Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Stripe processes over $1T in payments volume per year, which is roughly 1% of the world’s GDP. The tremendous amount of data makes Stripe one of the best places to do machine learning. The ML Infra team builds services and tools that power every step in the ML lifecycle, including data exploration, feature generation, experimentation, training, deploying, serving ML models, and building LLM applications. With the phenomenal developments happening in the field of AI, we are positioned to accelerate the adoption of AI/ML across all parts of the company by building highly scalable and reliable foundational infrastructure.

What you’ll do

You will work closely with machine learning engineers, data scientists, and product engineering teams to enable seamless end-to-end experience in building solutions across data, analytics, and AI/ML platforms. You will build the next generation of ML Infra services and major new capabilities that substantially improve ML development velocity and MLOps maturity across the company.

Responsibilities 

• Designing and building scalable, reliable, and secure services for notebooks, ML model training, experimentation, serving, and LLM applications across multiple regions. 
• Creating services and libraries that enable ML engineers at Stripe to seamlessly transition from experimentation to production across Stripe’s systems. 
• Working directly with product teams and ML engineers to improve their day-to-day productivity. 
• Taking ownership of and finding solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies.

Who you are

We’re looking for people with a strong background or interest in building successful products or systems; you’re passionate about solving business problems and making impact, you are comfortable in dealing with lots of moving pieces; and you’re comfortable learning new technologies and systems. You are comfortable working with other Stripe teams across the US and Canada.

Minimum requirements

• 2+ years of professional software development experience with a solid background on service oriented architecture and large-scale distributed systems
• Experience working through the full life cycle of software development, from talking to users, to design and implementation, to testing and deployment, to operations
• Experience working on production ML platforms, MLOps solutions, or building LLM applications
• Experience running operations for high availability, low latency systems
• Experience partnering with other teams to drive business outcomes
• A sense of pragmatism: you know when to aim for the ideal solution and when to adjust course

Preferred qualifications 

• Experience building and shipping production AI agents
• Familiarity with the LLMs and LLM Frameworks
• Experience training and shipping machine learning models to production to solve critical business problems

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in Canada.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

What You'll Do

• ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
• HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Who Should Apply

• Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
• Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
• Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.

Why Join the HFC?

• Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
• Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. 

Application Process

1. Apply: We review applications on a rolling basis.
2. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
3. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

Customer Experience:

The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused professional to join our team as a Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work remotely from the US or Canada.

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

Key Employee Benefits:

• Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) Plan: Up to 4% company match with immediate vesting.
• Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote Work Reimbursement: Up to $85/month for mobile and internet.
• Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.

Compensation

We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.

Join Nebius Today!

Customer Experience:

The Customer Experience Team at Nebius AI Cloud involves tackling customers’ challenges and directly impacting their success by solving real-world AI and ML problems at massive GPU cloud scale. You’ll not only resolve issues, but play a key role in shaping clients’ business success by optimizing their AI solutions. Working with advanced GPUs such as H200, B200 and GB200, as well as modern ML frameworks, you’ll influence the development of the Nebius AI Cloud and gain experience at the intersection of infrastructure and AI. With minimal bureaucracy, you’ll have the freedom to innovate, take ownership and drive change. Opportunities for growth are abundant in this vibrant and supportive professional community.

The role

We are seeking a highly skilled and customer-focused professional to join our team as a AI/ML Specialist Solutions Architect specializing in Cloud infrastructure and MLOps. As a Cloud Solutions Architect, you will play a pivotal role in designing and implementing cutting-edge solutions for our clients, leveraging cloud technologies for ML/AI teams and becoming a trusted technical advisor for building their pipelines.

You’re welcome to work remotely from the US or Canada.

Your responsibilities will include: 

• Act as a trusted advisor to our clients, providing technical expertise and guidance throughout the engagement. Conduct PoC, workshops, presentations, and training sessions to educate clients on GPU cloud technologies and best practices.
• Collaborate with clients to understand their business requirements and develop solution architecture that align with their needs: design and document Infrastructure as code solutions, documentation and technical how-tos in collaboration with support engineers and technical writers.
• Help customers to optimize pipeline performance and scalability to ensure efficient utilization of cloud resources and services powered by Nebius AI.
• Act as a single point of expertise of customer scenarios for product, technical support, marketing teams.
• Assist to Marketing department efforts during events (Hackathons, conferences, workshops, webinars, etc.)

We expect you to have: 

• 5 - 10 + years of experience as a cloud solutions architect, system/network engineer, developer or a similar technical role with a focus on cloud computing
• Strong hands-on experience with IaC and configuration management tools (preferably Terraform/Ansible), Kubernetes, skills of writing code in Python
• Solid understanding of GPU computing practices for ML training and inference workloads, GPU software stack components, including drivers, libraries (e.g. CUDA, OpenCL)
• Excellent communication skills
• Customer-centric mindset

It will be an added bonus if you have: 

• Hands-on experience with HPC/ML orchestration frameworks (e.g. Slurm, Kubeflow)
• Hands-on experience with deep learning frameworks (e.g. TensorFlow, PyTorch)
• Solid understanding of cloud ML tools landscape from industry leaders (NVIDIA, AWS, Azure, Google) 

Key Employee Benefits:

• Health Insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
• 401(k) Plan: Up to 4% company match with immediate vesting.
• Parental Leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
• Remote Work Reimbursement: Up to $85/month for mobile and internet.
• Disability & Life Insurance: Company-paid short-term, long-term, and life insurance coverage.

Compensation

We offer competitive salaries, ranging from 225k - 315k OTE (On-Target Earnings) and equity based on your experience, skills, and location.

Join Nebius Today!

Role & Team

We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.

As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.

Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.

This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.

Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)

What You'll Do 

• Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
• Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
• Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
• Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
• Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
• Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
• Set metrics and accountability for platform performance, reliability, and developer productivity

Skills & Experience

• 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
• Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
• Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
• A track record of building reliable, scalable systems used by fast-moving product teams
• Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
• Strong communication skills and the ability to influence across org boundaries
• Experience in data- or ML-heavy products

Nice To Have

• Experience with geospatial data, image processing or mapping technology 

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits.  
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

Role & Team

As a Staff Machine Learning Engineer at Overstory, you will lead the development and scaling of our Wildfire Fuel Detection Model. This core engine powers how we understand vegetation structure, fuel loads, and wildfire risk from satellite and environmental data. You’ll help shape the next generation of Overstory’s modeling capabilities by combining cutting-edge ML techniques, large-scale geospatial data, and real-world domain expertise.

Reporting to our VP of Product Engineering, you’ll work closely with data scientists, ML engineers, and product teams to ensure our wildfire models are accurate, robust, and production-ready – balancing scientific rigor with practical engineering excellence. As a senior technical leader, you’ll mentor other engineers, drive architectural decisions, and define standards for modeling, experimentation, and deployment across Overstory.

Time zone requirement: Eastern North America (NST, AST, EST)

What You’ll Do

In collaboration with data, ML, and science colleagues, you will:

• Architect and build advanced ML models to map and predict vegetation and fuel conditions across diverse geographies.
• Design and maintain robust data and feature pipelines for large-scale geospatial and temporal data.
• Partner with wildfire science and product teams to define modeling objectives and evaluation metrics tied to real-world impact.
• Build reproducible experimentation frameworks and model evaluation workflows.
• Scale models from research to production with a focus on performance, reliability, and explainability.
• Lead the evolution of ML systems, tooling, and processes — ensuring that our wildfire fuelscape models remain state-of-the-art and maintainable.
• Collaborate with MLOps peers to streamline training, inference, and monitoring in production environments.

Skills & Experience

• Experience thriving at the intersection of machine learning, geospatial data, and environmental science; deeply motivated by the opportunity to reduce wildfire risk through data-driven insights
• 10+ years of experience designing and building production-grade ML pipelines and systems 
• Strong background in deep learning, computer vision, or remote sensing
• Skilled in designing end-to-end ML systems — from data ingestion and preprocessing to deployment and monitoring
• Hands-on experience with frameworks like PyTorch, TensorFlow, XGBoost, or LightGBM, and data tools like Dask, Spark, or GeoPandas
• Familiarity with GCP and Vertex AI, or similar cloud-based ML platforms
• Strong communication skills and ability to collaborate across technical and scientific domains
• Comfortable leading architectural discussions and mentoring other engineers

Nice To Have

• Background in wildfire science, forestry, or remote sensing
• Experience integrating physics-based models with ML or working with active learning and uncertainty quantification
• Experience in model interpretability and data provenance for environmental ML systems
• Experience with deep learning models for weather or climate data
• Experience in remote-first or globally distributed teams

Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.

What We Offer

• Competitive, location-specific compensation and benefits 
• Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
• Home office stipend, coworking and ongoing education budgets 
• A company culture that genuinely embodies each of our core values
• To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis

The Growth Tech Alliance's goal is to enable HelloFresh to drive smarter marketing through AI-powered automation, intelligent systems, and advanced optimization. We've pioneered cutting-edge approaches to programmatic campaign optimization using state-of-the-art AI/ML technologies and are now scaling these capabilities across our global marketing operations. Our team’s key responsibilities include designing, building, maintaining autonomous decision-making systems, advanced ML models for marketing optimization, and real-time intelligence that drives measurable business impact. We work at the intersection of modern AI architectures, deep statistical modelling, and enterprise-scale ML operations.

S'more about the team

As a Senior Data Scientist in AdTech, you will design, build, and deploy production-grade machine learning models that drive significant marketing ROI. You will provide critical expertise in advancing our intelligent marketing optimization systems, focusing on the entire ML lifecycle from data preprocessing and feature engineering to large-scale deployment and performance monitoring. By translating complex marketing challenges into robust production systems, you will ensure our AI-driven capabilities deliver measurable business impact and enhanced efficiency at a  global scale

Lettuce share what this role will be responsible for

• Develop, build, and iterate on advanced machine learning models across core adtech domains to optimize marketing performance and contribute to the orchestration of highly efficient marketing workflows.
• Design and implement ML models for Media Optimization, and contribute to their operationalization into high-impact production systems.
• Contribute to Creative Automation efforts by building and enhancing predictive AI models to guide our global production studios.
• Design and build ML models for Value Optimization to intelligently isolate high-value customers.
• Adhere to and contribute to the team's ML operations (MLOps) practices, focusing on experiment tracking, system observability, and model reliability in production.
• Rapidly prototype innovative machine learning solutions, including Gen AI-forward approaches, and integrate them into our existing, orchestrated multi-agent systems to enable complex autonomous workflows.
• Collaborate closely with Product, Engineering, and Marketing to identify high-impact programmatic automation opportunities and execute robust A/B testing and experimentation designs for models in high-noise environments.
• All other duties, as assigned

Sound a-peeling? Here's what we're looking for

• MSc or equivalent experience in a quantitative discipline with proven experience building and deploying AI/ML systems from prototype to production at scale
• Expert proficiency in Python, PySpark, and SQL, hands-on experience with cloud environments (GCP, AWS, or Azure), and practical experience with modern machine learning frameworks such as HuggingFace, TensorFlow or similar.
• Expertise in applied machine learning relevant to AdTech, including predictive modeling, optimization algorithms, and modern LLM capabilities preferred.
• Proven experience tackling complex marketing data problems, such as algorithmic budget pacing, LTV prediction pipelines, or AI-driven media optimization systems.
• Strong foundation in statistical analysis and experimentation, with practical experience designing A/B tests to validate the incremental business impact of algorithmic systems
• Demonstrated ability to effectively communicate intricate analytical findings to diverse audiences, bridging the gap between deep technical implementation and core business KPIs
• Track record of building production ML systems with robust practices, demonstrating a bias for action and extreme ownership, treating the business outcomes of your algorithms with a true Founder Mentality
• Experience with programmatic advertising ecosystems, marketing analytics, and the operational aspects of running performance-critical ML models in high-traffic environments

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

About the Job

Do you get excited when a messy, ambiguous business problem finally yields to the right model? Do you think in systems, speak fluently across the technical-business divide, and want your work to do more than sit in a notebook — you want it to actually ship, scale, and matter?

With over 2,000 employees, 36 offices on five continents, and world-class clients like Samsung, L'Oréal, and Mattel, Artefact is a consulting firm that transforms data into measurable value and business impact. We're growing our Canadian presence and want you to join us as a technical cornerstone of our founding team in Canada.

Who We Are

Founded and headquartered in Paris, Artefact is a next-generation consulting firm specializing in data, analytics, and AI consulting — dedicated to transforming data into business impact across the entire value chain of organizations. We don't just advise; we build, implement, and deliver results our clients can measure.

We have 2,000 employees across 36 offices focused on accelerating digital transformation for some of the world's most recognizable brands. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of elite business consultants, data analysts, data scientists, data engineers, and digital experts are all laser-focused on delivering real value to every client. We design data-driven solutions tailored to each client's specific needs — always conceived with a business-first mindset and delivered with tangible, measurable results. Our expertise is built on deep AI knowledge acquired through 1,000+ client engagements across the globe.

Find out more at artefact.com.

What You Will Be Doing

As a Senior Data Scientist, you'll be the technical engine behind some of our most complex and consequential client engagements in Canada. You'll move fluidly between data exploration, model development, and executive communication — bringing scientific rigor to business problems and translating results into strategies that clients actually implement.

This isn't a role where you hand off findings and walk away. You'll be embedded with clients across Canada's most dynamic sectors — financial services, retail, CPG, telecoms, media, and the public sector — co-owning outcomes and ensuring that the models you build don't just perform in a test environment, they create real, lasting impact in production. You'll also be a technical anchor for our Canadian team, setting standards, mentoring junior data scientists, and contributing to the methodologies that define Artefact's edge in this market.

Key responsibilities include:

• Designing and building end-to-end machine learning and statistical models that solve high-stakes business problems — from framing the question to deploying the solution
• Conducting rigorous exploratory data analysis to uncover patterns, anomalies, and opportunities that inform both technical and strategic decisions
• Translating complex model outputs and analytical findings into clear, compelling narratives for senior client stakeholders — making the technical accessible without dumbing it down
• Partnering with client teams and data engineers to ensure models are production-ready, scalable, and built on clean, reliable data pipelines
• Defining the analytical approach for client engagements — selecting the right methods, tools, and frameworks for the problem at hand, not just the ones you're most comfortable with
• Contributing to new business proposals — helping articulate Artefact's technical capabilities and translating data science into clear client value
• Developing thought leadership and internal methodologies — publishing research, building reusable frameworks, and raising the technical bar across the Canadian practice
• Mentoring junior data scientists and analysts, actively investing in the team's technical depth and growth

What We Are Looking For

We want someone who is as comfortable whiteboarding a modeling strategy with a client's Chief Analytics Officer as they are debugging a pipeline before a critical delivery. You've shipped models that people actually use. You've sat in rooms where the business stakes were real, and you've delivered. You know the difference between a technically elegant solution and a practically useful one — and you always choose useful.

You'll arrive ready with the following:

• 4–7 years of hands-on experience in data science, machine learning, or advanced analytics — with a demonstrable track record of end-to-end model delivery in a client-facing or high-stakes business environment
• Advanced degree (MSc or PhD) in a quantitative field — statistics, mathematics, computer science, engineering, or equivalent; strong undergraduate candidates with exceptional experience will be considered
• Expert-level proficiency in Python and/or R; you write clean, maintainable, production-quality code
• Deep expertise in machine learning and statistical modeling — regression, classification, clustering, time series, NLP, recommendation systems, and/or deep learning, depending on your specialization
• Strong command of SQL and experience working with large-scale datasets across cloud platforms (GCP, AWS, or Azure)
• Experience with MLOps practices — model versioning, monitoring, deployment pipelines, and productionization — is a significant differentiator
• Exceptional communication skills — you can explain a gradient boosting model to a CFO and a business case to an ML engineer, and both conversations land
• Demonstrated ability to lead technical workstreams and mentor junior team membersBilingualism (English/French) is a significant asset, particularly for client engagement in Quebec and federal government contexts
• Consulting or client-facing experience is highly desirable; the ability to manage ambiguity, scope problems, and deliver under pressure is essential
• Familiarity with Canada's data privacy regulatory landscape — PIPEDA, Quebec's Law 25, and sector-specific frameworks in financial services and healthcare — is a meaningful differentiator
• Exposure to marketing analytics, customer analytics, fraud detection, risk modeling, or demand forecasting within Canadian financial services, retail, or CPG is a strong asset

Why You Should Join Us

At this level, you're not just looking for a job — you're looking for the right environment to do your best work. Here's what makes Artefact different:

Variety that keeps you sharp. In a product role, you go deep on one problem. Here, you'll work across Canada's most dynamic industries and business functions — building the kind of range that makes exceptional data scientists truly exceptional. No two engagements are the same.

Your work actually ships. We have a relentless focus on adoption and impact. The models you build are designed from day one to live in production, influence decisions, and create measurable value — not to gather dust in a final report.

A global technical community, with local roots. With 2,000 data and AI specialists across 36 offices worldwide, you'll have access to some of the most sophisticated data science thinking on the planet — while building something meaningful right here in Canada. You'll bring global best practices to the Canadian market and contribute Canadian insights back to the world.

Founding team energy. We're building our Canadian practice, which means the standards, culture, and technical identity you help create now will define Artefact in this market for years to come. That's a rare opportunity at any stage of a career.

We are united by our values and strengthened by our hybrid expertise:

There is always a way — We're builders, diggers, and makers. Ideas only count if they get executed.
Client trust is won in the field — We show up where it matters, working side by side with our clients to solve what's real.
If not used, it is useless — We build for adoption and impact. True brilliance is measured by what changes, not what's delivered.
If not shared, our work is not done — Sharing knowledge is how we close the loop — for our clients and for each other.
We learn every day — In a field moving at the speed of light, intellectual curiosity isn't optional. It's survival.

Overview: 

Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. 

This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. 

Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services.

This is a hybrid position based in Toronto. 

What You'll Do 

• Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. 

• Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production environments like Databricks and Azure Kubernetes Service (AKS). 

• Optimize RAG Pipelines: Continuously improve retrieval and generation quality through techniques like retrieval optimization (tuning k-values, chunk sizes), using re-rankers, advanced chunking strategies, and prompt engineering for hallucination reduction. 

• Integrate Intelligent Systems: Engineer solutions that seamlessly combine LLMs with our proprietary knowledge repositories, external APIs, and real-time data streams to create powerful copilots and research assistants. 

• Champion LLMOps and Engineering Best Practices: Collaborate with data science and engineering teams to establish and implement best practices for LLMOps, including automated evaluation using frameworks like LLM Judges or MLflow, AI observability, and system monitoring. 

• Evaluate and Implement AI Strategies: Systematically evaluate and apply advanced prompt engineering methods (e.g., Chain-of-Thought, ReAct) and other model interaction techniques to optimize the performance and safety of proprietary and open-source LLMs. 

• Mentor and Lead: Provide technical leadership to junior engineers through rigorous code reviews, mentorship, and design discussions, helping to elevate the team's engineering standards. 

• Influence the Roadmap: Partner closely with product and business stakeholders to translate user needs into technical requirements, define priorities, and shape the future of our AI product offerings. 

 What You'll Bring 

• Experience: A Bachelor’s degree in Computer Science, Engineering, or a related technical field with 6+ years of professional experience; or a Master’s degree with 4+ years of professional experience in backend software engineering and Generative AI. This must include a proven track record of designing, building, and scaling distributed, production-grade systems. 

• Strong Software Engineering Fundamentals: Deep expertise in Python, a major backend framework (e.g., FastAPI, Flask), and asynchronous programming (e.g., asyncio). Proficiency in designing RESTful APIs, microservices, and the complete operational lifecycle, including comprehensive testing, CI/CD (e.g., ArgoCD), observability, monitoring, alerting, maintaining high uptime, and executing zero-downtime deployments. 

• Cloud & Infrastructure Proficiency: Hands-on experience deploying and managing applications on a major cloud platform (Azure preferred, AWS/GCP acceptable) using containerization (Docker) and orchestration (Kubernetes, Helm). 

• Production AI Application Experience: 2+ years of experience building applications that leverage large language models from providers like OpenAI, Anthropic, or Google Gemini. Direct experience with modern LLM patterns such as retrieval-augmented generation (RAG), hybrid search using vector databases (e.g., Pinecone, Elasticsearch), multi-agent AI systems with tool calls, and prompt engineering is required. 

• AI System Design and Evaluation: Experience designing and implementing robust evaluation frameworks for LLM-based systems, including rubric-based scoring, LLM Judges, or using tools like MLflow, alongside monitoring for performance and drift. 

• Large-Scale Data Processing: Familiarity with large-scale data processing platforms and tools (e.g., Databricks, Apache Spark). 

• Familiarity with the Modern AI Stack: Practical experience with libraries and frameworks like LangChain or LlamaIndex for building LLM-powered applications. 

• Leadership and Mentorship: Demonstrated ability to lead complex technical projects and foster the growth of other engineers. 

What We Offer:  

The annual base salary range for this position is $135,000 - $210,000. Additionally, this position is eligible for an annual discretionary bonus based on performance.

You will also be eligible for the following benefits: 

• Paid Time Off 

• Comprehensive benefits plan 
• Company RRSP Match 
• Development opportunities through the LinkedIn Learning platform 

About Guidepoint: 

Guidepoint is a leading research enablement platform designed to advance understanding and empower our clients’ decision-making process. Powered by innovative technology, real-time data, and hard-to-source expertise, we help our clients to turn answers into action. 

Backed by a network of nearly 1.75 million experts, and Guidepoint’s 1,600 employees worldwide, we inform leading organizations’ research by delivering on-demand intelligence and research on request. With Guidepoint, companies and investors can better navigate the abundance of information available today, making it both more useful and more powerful. 

At Guidepoint, our success relies on the diversity of our employees, advisors, and client base, which allows us to create connections that offer a wealth of perspectives. We are committed to upholding policies that contribute to an equitable and welcoming environment for our community, regardless of background, identity, or experience. 

#LI-SP1

#LI-Hybrid

About the Role

We’re hiring an AI Solutions Architect to lead the future of IT systems and automation at Fortis. This senior-level role focuses on improving how our internal tech works — using AI, automation, and innovative design to make everything more secure, scalable, and efficient.

You’ll lead the design of our IT tools and platforms, ensuring they’re modern, user-friendly, and powered by cutting-edge AI like LLMs (think ChatGPT, Gemini, and similar tools). This role reports to the Director of IT. It works closely with Security, Legal, Engineering, and other departments to ensure our IT systems are robust, safe, compliant, and built to scale.

This isn’t just an execution or admin role — it’s a leadership position for someone who can research, propose, and help drive future-focused IT strategies across the business.

What You'll Achieve

• Define and implement scalable, secure, AI-driven IT architectures aligned with business needs.
• Research, propose, and implement AI/LLM-based automation for IT processes, support systems, and knowledge management.
• Lead AI initiatives and strategy sessions, chairing technology trend discussions and quarterly IT innovation reviews.
• Architect and deploy cloud-native, automation-first IT systems — focused on resilience, performance, and zero-touch management.
• Implement AI-powered IT service desk solutions, compliance monitoring, incident response, and proactive issue resolution.
• Guide IT Operations in optimizing hardware lifecycle, SaaS platforms, and IT asset tracking through AI/automation-driven efficiency.
• Collaborate closely with Security and Legal teams to align AI and IT architecture with compliance, risk management, and privacy standards.
• Drive tool rationalization and consolidation projects using AI analytics to inform more intelligent decision-making.
• Partner with engineering, AI/ML teams, and vendors to integrate IT systems into our broader AI development ecosystem.

What You’ll Need to Be Successful

• Solid experience in IT engineering, IT architecture and cloud-native systems — with a recent, strong focus on AI, automation, and LLMs.
• Experience with AI technologies like large language models (LLMs), MLOps tools, and generative AI platforms (e.g., ChatGPT/OpenAI, Gemini AI, Notion AI). You’ve used these tools to help build or improve systems, not just test them.
• Practical experience building, integrating, or experimenting with AI models, LLMs, and AI-driven workflows.
• Working knowledge of enterprise IT environments, including Google Workspace, Okta, JAMF, Intune, Zoom, Slack, and Cisco Meraki, plus an understanding of cloud infrastructure (AWS, GCP, or Azure).
• Exceptional skills in technical documentation, architecture diagramming, and project planning and execution, plus an understanding of  GDPR, NIST, and SOC 2.
• Ability to explain complex technology and AI clearly and simply to all audiences. Skilled at leading conversations that shape the right technology direction, drive innovation, and bring new ideas to life. 
• Confident in leading executive meetings, managing AI committees, and guiding leadership teams toward smart, forward-thinking technology decisions.
• Game/software development experience strongly preferred where LLMs or automation were part of the tech stack, showcasing creativity, speed, and next-gen thinking.

We are a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca, AutoSync, Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence. 

AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond.

What's in it for you:

We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from that support us to be our creative best. 

• Gym discounts 

• Employee and Family Assistance program 

• Virtual wellness events 

• Conferences & training budget 

• Regular internal training programs 

• Financial planning with 3% matching Pension  

• Competitive salary 
• Annual bonus structure 

For a career where you can drive our business and shape your future, apply now. 

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the opportunity

We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization. 

What You Will Be Doing

• Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
  
  
• Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
  
  
• Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
  
  
• Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
  
  
• Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
  
  
• Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
  
  
• Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
  
  
• Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.

What You Bring

• Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
  
  
• Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
  
  
• SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
  
  
• dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
  
  
• Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
  
  
• Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
  
  
• Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
  
  
• AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
  
  
• Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
  
  
• Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
  
  
• ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
  
  
• Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
  
  
• Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
  
  
• Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
  
  
• Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
  
  
• Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.

Nice to Have

• Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
  
  
• AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
  
  
• Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
  
  
• Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
  
  
• Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.

The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.

This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.

If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!

​​The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits. 

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you’ve never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It’s also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd! 

About the opportunity

We are seeking an experienced and versatile Analytics Engineer to join our dynamic team. In this role, you will apply your advanced analytics expertise to extract actionable insights from raw data. The ideal candidate will have a strong background in data engineering, analytics, and machine learning, with the ability to drive data-driven decision-making across the organization. 

What You Will Be Doing

• Data Modeling & Pipelines: Design, develop, and maintain complex data models in our Snowflake data warehouse. Utilize dbt (Data Build Tool) to create efficient data pipelines and transformations for our data platform.
  
  
• Snowflake Intelligence Integration: Leverage Snowflake Intelligence features (e.g., Cortex Analyst, Cortex Agents, Cortex Search, AISQL) to implement conversational data queries and AI-driven insights directly within our data environment. Develop AI solutions that harness these capabilities to extract valuable business insights.
  
  
• Advanced SQL & Analysis: Design and build advanced SQL queries to retrieve and manipulate complex data sets. Dive deep into large datasets to uncover patterns, trends, and opportunities that inform strategic decision-making.
  
  
• Business Intelligence (BI): Develop, maintain, and optimize Looker dashboards and LookML to effectively communicate data insights. Leverage Looker’s conversational analytics and data agent features to enable stakeholders to interact with data using natural language queries.
  
  
• Cross-Functional Collaboration: Communicate effectively with stakeholders to understand business requirements and deliver data-driven solutions. Identify opportunities for implementing AI/ML/NLP technologies in collaboration with product, engineering, and business teams.
  
  
• Programming & Automation: Write efficient Python code for data analysis, data processing, and automation of recurring tasks. Skilled in shell scripting and command-line tools to support data workflows and system tasks. Ensure code is well-tested and integrated into automated workflows (e.g., via Airflow job scheduling).
  
  
• Visualization & Presentation: Create compelling visualizations and presentations to deliver analytical insights and actionable recommendations to senior management and cross-functional teams. Tailor communication of complex analyses to diverse audiences.
  
  
• Innovation & Best Practices: Stay up-to-date with industry trends, emerging tools, and best practices in data engineering and analytics (with a focus on dbt features, Snowflake’s latest offerings and BI innovations). Develop and implement innovative ideas to continuously improve our analytics stack and practices.

What You Bring

• Education: Bachelor’s degree in Computer Science, Statistics, or a related field; Master’s degree preferred.
  
  
• Experience: 2+ years of experience in data analytics or a related field, with significant exposure to AI and Machine Learning applications in analytics.
  
  
• SQL Expertise: Advanced SQL skills with experience in writing and optimizing complex queries on large-scale datasets.
  
  
• dbt Proficiency: Hands-on experience with dbt (Data Build Tool) and its features for building, testing, and documenting data models.
  
  
• Data Modeling: Expert-level knowledge of data modeling and data warehouse concepts (e.g., star schema, normalization, slowly changing dimensions).
  
  
• Snowflake & AI Capabilities: Experience with Snowflake’s Data Cloud platform and familiarity with its advanced AI capabilities (Snowflake Intelligence – Cortex Analyst, Cortex Agents, Cortex Search, AISQL, etc.) is highly preferred.
  
  
• Business Intelligence Tools: Strong skills in Looker data visualization and LookML (including familiarity with Looker’s conversational AI and data agent capabilities) or similar BI tools.
  
  
• AI Agents & Automation: Experience with AI agents or generative AI tools to optimize workflows and service delivery (such as creating chatbots or automated analytic assistants) is a plus.
  
  
• Real-Time & Streaming Data: Experience with real-time data processing and streaming technologies (e.g., Kafka, Kinesis, Spark Streaming) for handling continuous data flows.
  
  
• Programming: Proficient in Python for data analysis and manipulation (pandas, NumPy, etc.), with the ability to write clean, efficient code. Experienced with shell scripting and command-line tools for automating workflows and data processing tasks.
  
  
• ETL/Orchestration: Familiarity with ETL processes and workflow orchestration tools like Apache Airflow (or similar scheduling tools) for automating data pipelines alongside Docker for local development and testing.
  
  
• Cloud Platforms: Experience with cloud platforms and services (especially AWS or GCP) for data storage, compute, and deployment.
  
  
• Version Control & CI/CD: Solid understanding of code versioning (Git) and continuous integration/continuous deployment (CI/CD) processes in a data engineering context.
  
  
• Agile Methodology: Familiarity with agile development methodologies and ability to work in a fast-paced, iterative environment.
  
  
• Soft Skills: Excellent communication and presentation skills, with critical thinking and problem-solving abilities. Proven track record of working effectively on cross-functional teams and translating business needs into technical solutions.
  
  
• Data Governance & Ethics: Experience implementing data governance best practices, ensuring data quality and consistency. Knowledge of data ethics, bias mitigation strategies, and data privacy regulations (e.g., GDPR, CCPA) with a commitment to compliance.

Nice to Have

• Community & Open Source: Contributions to open-source projects or active participation in data community initiatives.
  
  
• AI/ML Skills: Experience with applying Artificial Intelligence/Machine Learning techniques in analytics (e.g., building predictive models for forecasting, churn prediction, fraud detection, etc.). Practical experience deploying models and using MLOps/DataOps practices for lifecycle management.
  
  
• Statistical Background: Solid foundation in statistics and probability, with ability to apply various modeling techniques and design A/B tests or experiments.
  
  
• Additional Programming: Knowledge of additional programming or query languages (e.g., R, Scala, Julia, Spark SQL) that can be applied in analytics workflows.
  
  
• Certifications: Certifications in relevant data technologies or cloud platforms (such as Snowflake, AWS, GCP, or Looker) demonstrating your expertise.

The ideal candidate will be a self-starter with a passion for data and analytics, capable of navigating complex datasets to uncover valuable insights. They should be comfortable working in a fast-paced environment, adapting to new technologies, and driving innovation in our data practices.They should be able to navigate complex data landscapes, uncover meaningful insights, and communicate these findings effectively to both technical and non-technical audiences. The ability to stay current with industry trends and continuously learn new technologies is essential in this role.

This role offers the opportunity to make a significant impact on our organization's data strategy and contribute to critical business decisions through advanced analytics. The successful candidate will play a key role in shaping our data culture and driving the adoption of cutting-edge data technologies and methodologies.

If you are a data enthusiast with a track record of delivering impactful analytics solutions and a desire to push the boundaries of what's possible with data, we want to hear from you!

​​The base salary range for this position is $81,990 to $91,100. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous benefits. 

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.

Concevoir et bâtir des solutions axées sur l’IA qui propulsent la prochaine génération de plateformes d’entreprise intelligentes.

Le poste

À titre d’ingénieur en IA, vous concevrez et développerez des solutions axées sur l’IA qui améliorent les plateformes numériques et permettent une prise de décision intelligente dans les environnements d’entreprise. En vous appuyant sur votre solide expérience en ingénierie logicielle, vous appliquerez des approches modernes en IA pour créer des systèmes évolutifs, adaptables et performants. Vous travaillerez en étroite collaboration avec des équipes interfonctionnelles, notamment Produit, Architecture et Ingénierie, afin de livrer des solutions innovantes alignées sur les besoins des clients.

Ce que vous ferez

• Concevoir et développer des applications et des services axés sur l’IA, en mettant à profit votre expertise de base en ingénierie logicielle
• Appliquer des approches modernes en IA/AA pour améliorer les capacités des systèmes et permettre l’automatisation intelligente
• Collaborer avec des équipes interfonctionnelles pour aligner les solutions d’IA sur les exigences commerciales et opérationnelles
• Contribuer à la conception des systèmes, à l’architecture et à l’intégration des composants d’IA dans les plateformes d’entreprise
• Soutenir l’amélioration continue par l’expérimentation, les tests et l’optimisation des performances des solutions d’IA

Ce que nous recherchons

• 5 à 8 ans d’expérience en développement logiciel dans divers langages de programmation modernes
• Transition démontrée vers la conception et le développement axés sur l’IA, avec application des concepts d’IA/AA à des solutions concrètes
• Solide compréhension des principes de conception axés sur l’IA et du développement de systèmes évolutifs
• Capacité à évaluer et à appliquer les technologies appropriées en fonction du contexte du problème
• Excellentes aptitudes en communication et capacité à collaborer avec des équipes techniques et non techniques

Atouts supplémentaires

• Expérience de travail avec des plateformes infonuagiques (p. ex., Azure) pour le déploiement de solutions d’IA
• Connaissance des pratiques MLOps et de la gestion du cycle de vie des modèles d’IA
• Expérience d’intégration de solutions d’IA dans des environnements d’entreprise ou de services financiers
• Expérience en ingénierie des données, en pipelines de données ou en traitement de données à grande échelle
• Compréhension de l’IA responsable, de la gouvernance des modèles et des pratiques éthiques en matière d’IA
• Maîtrise du français et de l’anglais
• Étant donné que la majorité de nos clients et collègues sont situés à l’extérieur du Québec et du Canada, des exigences linguistiques particulières peuvent s’appliquer et une maîtrise professionnelle de l’anglais est requise.

Pourquoi rejoindre Capco

• Livrer des solutions technologiques à fort impact pour des institutions financières de premier ordre
• Travailler dans une culture de consultation collaborative, horizontale et entrepreneuriale
• Accéder à de la formation continue, à de l’apprentissage et à des certifications de l’industrie
• Faire partie d’une équipe qui façonne l’avenir des services financiers numériques
• Aider à façonner l’avenir de la transformation numérique dans les services financiers et l’énergie.

Utilisation de l’intelligence artificielle dans l’acquisition de talents

Chez Capco, nous utilisons des outils d’intelligence artificielle (IA) pour soutenir et améliorer plusieurs volets de l’acquisition de talents. Cela inclut l’utilisation de fonctions compatibles avec l’IA dans LinkedIn pour aider à repérer des candidats potentiels, accélérer les communications de recrutement courantes comme les courriels et créer des offres d’emploi convaincantes, alignées sur la marque et reflétant avec exactitude les exigences du poste, ainsi que des applications de planification par IA pour améliorer l’efficacité de la coordination des entrevues.

L’IA est utilisée uniquement comme outil de soutien. Toutes les décisions d’embauche sont prises par les équipes d’acquisition de talents et de recrutement.

Pourquoi ce poste est ouvert

Nous recrutons actuellement pour ce poste en raison d’un poste vacant existant ou nouvellement créé au sein de notre organisation. Ce poste est ouvert dans le cadre de nos besoins opérationnels continus, et nous examinons activement les candidatures afin de pourvoir ce poste avec une personne qualifiée qui pourra avoir un impact immédiat.

Nous offrons un ensemble d’avantages concurrentiel et axé sur les personnes, conçu pour soutenir tous les aspects de votre vie :

Avantages

• Couverture d’avantages complète – Assurance santé, vie et invalidité payée à 100 % par l’entreprise, en vigueur dès le premier jour d’emploi
• Régime d’épargne-retraite – Régime enregistré d’épargne-retraite (REER) avec option de cotisation de contrepartie de l’employeur
• Soins de santé virtuels – Programme payé par l’entreprise offert à tous les employés et à leurs personnes à charge/conjoints
• Programme d’aide aux employés et à leur famille (PAEF) – Services de soutien payés par l’entreprise pour les employés et leurs personnes à charge/conjoints
• Cadeau pour nouveau parent – Cadeau offert par l’entreprise pour célébrer l’arrivée d’un nouvel enfant
• Soutien au mieux-être – Remboursement des frais de conditionnement physique pour favoriser la santé et le bien-être
• Coach d’affaires dès le premier jour : Encadrement personnalisé en tête-à-tête pour soutenir l’évolution de carrière, accélérer le développement et aider à atteindre vos objectifs professionnels chez Capco.

L’inclusion chez Capco

Nous nous engageons à rendre notre processus de recrutement accessible et simple pour tout le monde. Si vous avez besoin d’un accommodement à n’importe quelle étape, faites-le-nous savoir — nous serons heureux de vous aider. Nous valorisons le point de vue et la contribution uniques de chaque personne. Chez Capco, nous croyons qu’être soi-même est votre plus grande force. Notre culture #SoyezVousMêmeAuTravail encourage l’individualité et la collaboration — un état d’esprit qui façonne la façon dont nous travaillons avec nos clients et entre nous chaque jour.

Transparence salariale

La fourchette salariale pour ce poste est indiquée ci-dessous. De plus, ce poste peut également être admissible à un paiement annuel de prime discrétionnaire/variable.

Capco s'engage à offrir une rémunération juste et équitable à son personnel. Nos politiques de rémunération et nos fourchettes salariales sont conçues pour permettre à nos employés de progresser dans la fourchette salariale à mesure qu'ils démontrent de solides performances et se développent dans leur rôle au fil du temps. Le salaire de base offert aux candidats retenus sera conforme à la fourchette salariale, et le placement variera en fonction de divers facteurs, y compris, mais sans s'y limiter, les connaissances, compétences, expérience et équité interne liées au poste.

CAD $118000 - CAD $152000

Design and build AI-first solutions that power the next generation of intelligent enterprise platforms.

The Role

As an AI Engineer, you will design and develop AI-first solutions that enhance digital platforms and enable intelligent decision-making across enterprise environments. Building on your strong software engineering background, you will apply modern AI approaches to create scalable, adaptable, and high-performing systems. You will work closely with cross-functional teams including Product, Architecture, and Engineering to deliver innovative solutions aligned to client needs.

What You’ll Do

• Design and develop AI-first applications and services, leveraging your core software engineering expertise
• Apply modern AI/ML approaches to enhance system capabilities and enable intelligent automation
• Collaborate with cross-functional teams to align AI solutions with business and operational requirements
• Contribute to system design, architecture, and integration of AI components into enterprise platforms
• Support continuous improvement through experimentation, testing, and performance optimisation of AI solutions

What We’re Looking For

• 5–8 years of software development experience across modern programming languages
• Demonstrated transition into AI-focused design and development, applying AI/ML concepts in real-world solutions
• Strong understanding of AI-first design principles and scalable system development
• Ability to evaluate and apply appropriate technologies based on problem context
• Strong communication skills with the ability to collaborate across technical and non-technical teams

Bonus Points For

• Experience working with cloud platforms (e.g., Azure) for AI solution deployment
• Familiarity with MLOps practices and lifecycle management of AI models
• Experience integrating AI solutions into enterprise or financial services environments
• Exposure to data engineering, data pipelines, or large-scale data processing
• Understanding of responsible AI, model governance, and ethical AI practices.
• Proficiency in French and English
• Given the majority of our clients and colleagues are located outside of Quebec and Canada, specific language requirements may apply and professional proficiency in English is required.
•  

Why Join Capco

• Deliver high-impact technology solutions for Tier 1 financial institutions
• Work in a collaborative, flat, and entrepreneurial consulting culture
• Access continuous learning, training, and industry certifications
• Be part of a team shaping the future of digital financial services
• Help shape the future of digital transformation across FS & Energy.

Use of Artificial Intelligence in Talent Acquisition

At Capco, we use artificial intelligence (AI) tools to support and enhance several parts of talent acquisition. This includes using AI-enabled features within LinkedIn to help source potential candidates, speeding up routine recruitment communications such as emails and creating compelling and brand-aligned job postings that accurately reflect role requirements, and AI-scheduling applications to improve the efficiency of interview coordination.

AI is used as a support tool only. All hiring decisions are made by talent acquisition and hiring teams.

Why This Role Is Open

We are currently hiring for this role due to an existing or newly created vacancy within our organization. This position is open as part of our ongoing business needs, and we are actively reviewing applications to fill this role with a qualified candidate who can make an immediate impact.

We offer a competitive, people-first benefits package designed to support every aspect of your life:

Benefits

• Comprehensive Benefits Coverage – 100% company-paid health, life, and disability insurance effective from Day 1 of employment
• Retirement Savings Program – Registered Retirement Savings Plan (RRSP) with the option of receiving a matching employer contribution
• Virtual Health Care – Company-paid program available to all employees and their dependents/partners
• Employee & Family Assistance Program (EFAP) – Company-paid support services for employees and their dependents/partners
• New Parent Gift – A company-sponsored gift to celebrate the arrival of a new child
• Wellness Support – Fitness reimbursement benefit to promote health and well-being
• Business Coach from Day 1: Personalized one-on-one coaching to support career growth, accelerate development, and help achieve your professional goals at Capco.

Inclusion at Capco

We’re committed to making our recruitment process accessible and straightforward for everyone. If you need any adjustments at any stage, just let us know – we’ll be happy to help. We value each person’s unique perspective and contribution. At Capco, we believe that being yourself is your greatest strength. Our #BeYourselfAtWork culture encourages individuality and collaboration – a mindset that shapes how we work with clients and each other every day.

#LI-hybrid

This is Engineering at Lattice

Lattice’s Engineering team is continuously improving both our product and our craft. We build maintainable, performant systems using modern technologies, and we collaborate closely with product and design to deliver agentic, high quality user experiences.

Our AI Engineering team is building the systems that power how AI works across Lattice. Within the Quality sub-team, we focus on how AI systems are evaluated, measured, and improved over time. You’ll contribute to the infrastructure and tooling that help us understand how our AI performs in production and ensure we’re building reliable, high-quality experiences for our customers.

What You Will Do

AI Evaluation & Quality Systems

• Contribute to AI evaluation pipelines, including offline evals, production tracing, and feedback systems.
• Implement and maintain performance metrics (e.g., response quality, task success, reliability) using established frameworks.
• Help create and maintain evaluation datasets and test cases to identify regressions.
• Analyze results and propose incremental improvements to model and agent quality.

AI Systems & Infrastructure

• Contribute to AI system components such as RAG pipelines, retrieval systems, and multi-step workflows within existing architectures.
• Write clean, maintainable Python code that integrates with LLM providers and internal services.
• Support improvements to system reliability, observability, and performance in production.

Execution & Team Contribution

• Deliver well-scoped projects with guidance from more senior engineers.
• Break down tasks, make steady progress, and be proactive in unblocking yourself by asking for help when needed.
• Contribute to team excellence through code reviews, documentation, and knowledge sharing
• Collaborate with cross-functional partners to ship user-facing features.

What You Will Bring to the Table

Experience

• 2–5 years of professional software engineering experience.
• Experience contributing to production systems as part of a team.
• Exposure to AI/ML systems with a strong interest in LLM-powered products.
• Experience debugging systems, working with data, and iterating on performance.

Technical Skills

• Proficiency in Python or a similar language.
• Strong understanding of LLM concepts (prompting, RAG, evaluation).
• Familiarity with backend systems, APIs, and cloud environments (e.g., AWS, GCP).
• Exposure to logging, monitoring, or debugging tools.
• Interest in learning tools like LangGraph, vector databases, and evaluation platforms.

Ways of Working

• Strong ownership: you reliably deliver high-quality work on well defined tasks, on time and communicate progress clearly.
• Learning mindset: you actively seek feedback and improve quickly. 
• Pragmatic and product-minded: you focus on solving problems effectively and not perfectly.
• Collaborative: you contribute to team discussions and uphold engineering best practices.
• Growth-oriented: you actively seek feedback and expand your skills in AI engineering.

Nice to Have

• Hands-on experience with LLMs, prompt iteration, or MLOps. 
• Familiarity with vector databases or retrieval systems.
• Exposure to experimentation, metrics, or basic statistical analysis.
• Familiarity with TypeScript. Our full-stack engineers use it and cross-pollination is valuable.

Location Requirement:
This role is open to candidates located in British Columbia or Ontario, Canada. At this time, we are only able to hire employees residing in these provinces.

The estimated annual cash salary for this role is CAD $90,000 - CAD $120,000. This position is also eligible for stock options, subject to the terms of Lattice’s applicable plans.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Life, AD&D, and Disability Insurance; Natural Disaster Support Program; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Working Remotely Stipend; One time WFH Office Set-Up Stipend; Retirement Plan; Financial Planning; and Learning & Development Budget.

Note on Pay Transparency:
Lattice provides an estimate of the compensation for roles that may be hired as required by regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

Lattice welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process.

#LI-Remote

What is The Role

At Elastic, we don’t just connect dots; we power the future of work. As the creators of Elasticsearch, Kibana, and Logstash, we are uniquely positioned to turn vast data into actionable intelligence. We are looking for a visionary Lead GenAI Cloud Developer to spearhead the evolution of ElasticGPT—transforming it from a conversational assistant into a proactive, task-oriented agentic ecosystem that removes friction from every Elastician's day.

Your Mission: From Chat to Action

You will lead the IT GenAI roadmap, moving beyond simple chat interfaces to build intuitive, action-oriented agentic workflows. Your goal is to mature our internal GPT tool’s (ElasticGPT) capabilities so it doesn't just answer questions—it executes tasks, automates complex processes, and serves as the primary driver of workforce productivity. 

This role requires experience building and operating real-world GenAI systems under constraints of scale, cost, latency, and enterprise governance—not just prototype or experimental workflows.

What You Will Be Doing

• AI Agent Strategy & Development: Lead the evolution of ElasticGPT into a task-oriented agent. Design sophisticated workflows (both agentic and deterministic) using LangGraph/LangChain/Elastic Agent Builder/n8n (or equivalent frameworks) to automate enterprise-wide productivity.
• Production RAG & Retrieval: Architect hybrid retrieval systems (BM25, vector search, RRF) using ESRE and Jina AI. Build data ingestion pipelines across Confluence, Jira, GitHub, and ServiceNow to improve answer quality.
• Infrastructure & MLOps: Oversee the full model lifecycle—from fine-tuning to deploying scalable APIs on Kubernetes—across major cloud providers (AWS, Azure, GCP).
• Optimization & Observability: Own token efficiency, latency, and cost management. Implement end-to-end tracing (OpenTelemetry) and evaluation pipelines to measure performance.
• Multi-Model Orchestration: Design and operate LLM gateway architectures for routing, fallback, spend control, and governance across multiple model providers.
• Protocol & Tool Architecture: Define multi-agent patterns, state management, tool contracts, and handoff logic for enterprise workflows. Demonstrate working knowledge of MCPs and modern agent tool-discovery patterns.
• Governance & Reliability: Design robust agents with retries, scoped permissions, and audit trails to ensure secure, reliable execution in a business tech stack.

What You Bring

• Advanced Agentic Expertise: Proven track record of building production-grade agents and RAG systems using frameworks like LangGraph/LangSmith.
• Technical Proficiency: Mastery of Python and TypeScript; deep experience with PyTorch, TensorFlow, or Hugging Face.
• Elasticsearch Mastery: Deep knowledge of ESRE, vector indexing (HNSW), and relevance tuning.
• System Design Intuition: Strong ability to balance the trade-offs between latency, cost, and response quality across multi-model environments (OpenAI, Anthropic, Vertex AI).
• Cloud & Scaling: Extensive experience with Kubernetes and managing high-concurrency cloud infrastructure.
• Strategic Ownership: A "builder" mindset with the ability to translate complex business needs into technical roadmaps and influence senior stakeholders.

• Education & Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • Proven experience in developing generative AI models, including Natural Language Processing (NLP) or computer vision models.
  • Proficiency in deep learning frameworks such as Microsoft Cognitive Services, TensorFlow, PyTorch, or Hugging Face Transformers.
  • Strong knowledge of cloud platforms and services (e.g., AWS, Azure, GCP).
  • Experience with containerization and orchestration (e.g., Docker, Kubernetes).
  • Knowledge of DevOps practices for model deployment and automation.
  • Strong problem-solving skills and the ability to work in a dynamic and fast-paced environment.
  • Excellent communication and collaboration skills.
  • A commitment to Ethical AI and responsible development practices.

#LI-JM5

As the Lead Product Marketing Manager, AI at GitLab, you'll shape how we bring our AI story to market across the software development lifecycle. You'll lead the narrative for GitLab Duo Agent Platform and related AI capabilities, helping customers understand how GitLab supports software teams and their AI agents in one platform. This role sits at the intersection of product, market insight, and revenue strategy, with a strong focus on positioning, messaging, launches, and monetization for AI offerings.

You'll work with significant autonomy while partnering closely with Product Management, Engineering, Sales, Customer Success, and Marketing. You'll bring firsthand experience using AI agents in your own marketing workflows — not just understanding them conceptually, but actively building with them to generate insights, pressure-test positioning, and accelerate your own work. That practitioner's lens is what will make your market narratives credible and your thought leadership distinctive. In your first year, you'll help refine our AI value proposition, strengthen how we speak to platform engineering and technology leaders, and turn market insight into repeatable go-to-market motions that support adoption and growth. You’ll also establish yourself as an emerging external voice on how AI agents are reshaping software teams — informed by your own hands-on use of agents workflows. 

Some examples of our projects:

• Developing and launching go-to-market strategies for GitLab Duo Agent Platform and AI offerings.
• Using AI agents to accelerate competitive analysis, synthesize customer feedback patterns, and generate first-draft positioning hypotheses — then sharing those methods as part of GitLab's thought leadership
• Creating persona-based messaging for organizations moving from individual AI coding tools to team and agent collaboration across the software lifecycle.
• Building thought leadership around intelligent orchestration, unified workflows, and how teams stay in flow with AI agents.
• Supporting launches for new AI capabilities, agentic workflows, and related monetization approaches.

What you'll do

• Collaborate on an end-to-end GTM strategy and execution for GitLab Duo Agent Platform and AI capabilities, emphasizing how intelligent orchestration enables software teams and their AI agents to stay in flow across the complete software lifecycle—addressing the "AI Paradox" where faster coding doesn't translate to faster delivery when the rest of the lifecycle remains fragmented.
• Lead positioning and narrative for GitLab's AI capabilities, articulating how we bring software teams and their AI agents together, eliminate gaps between traditionally-manual software lifecycle stages, and unify DevOps, Security, and AI workflows into a single orchestrated system where teams orchestrate from above while agents execute within. Your ability to articulate this vision will be strengthened by your own experience working alongside agents and understanding their capabilities and limitations firsthand.
• Develop and execute go-to-market strategies for usage-based AI monetization and consumption-based offerings that demonstrate clear customer value.
• Partner with Product Management, Sales, Customer Success, and Engineering to understand how customers are navigating AI modernization journeys, validate market problems around toolchain fragmentation and tool-specific AI agents, and translate them into clear messaging, revenue plays, pricing strategies, and launch priorities.
• Build and continuously refine compelling positioning and messaging for AI capabilities, including persona-specific content for platform engineering leaders, DevOps directors, technology executives, and developer teams.
• Define and execute comprehensive go-to-market plans for new AI capabilities, agents, workflows, and usage-based offerings, ensuring launches are timely, impactful, and tightly aligned with sales, field marketing, partner ecosystem, and digital marketing motions while delivering measurable pipeline and revenue impact.
• Serve as the subject matter expert for AI and intelligent orchestration within Product Marketing, synthesizing analyst feedback, market trends, competitive insights, and customer proof points into differentiated narratives that position GitLab's architectural advantages over AI coding tools and fragmented toolchain approaches.
• Create and maintain high-impact sales enablement materials such as pitches, playbooks, FAQs, objection-handling guides, use case libraries, and pricing and packaging comparison guides that help scale AI-focused sales motions and accelerate deal velocity.
• Build distinctive external thought leadership grounded in your own practice of using AI agents — sharing original insights from hands-on experimentation. You'll speak, write, and brief from a practitioner's perspective that gives GitLab's voice authenticity and specificity in a market full of abstract AI narratives.
• Partner with Product Marketing Managers on AI positioning, usage-based monetization, and go-to-market strategies within your area of expertise.
• Lead complex, cross-functional initiatives involving sales, product, growth, and marketing teams to drive AI adoption and revenue.

What you'll bring

• Strong product marketing experience owning complex, technical B2B SaaS products from discovery through launch, with proven success in usage-based monetization, consumption pricing models, and go-to-market strategies that drive measurable revenue impact in AI or developer tools markets.
• Deep understanding of AI/ML technologies, agentic workflows, LLM orchestration, and the software development lifecycle, with practical exposure to capabilities such as AI coding assistants, agentic automation, multi-agent systems, Model Context Protocol (MCP), and intelligent orchestration concepts.
• Demonstrated AI-first working style: you already use AI agents as core to how you develop positioning, conduct research, analyze competitors, and create content. You should be able to walk us through specific examples of insights you've generated or decisions you've made differently because of your agent-assisted workflow.
• Experience across multiple domains within DevSecOps, enabling you to position AI capabilities across the complete software lifecycle from planning through deployment and operations.
• Proven experience positioning platform solutions with ability to articulate architectural advantages of unified platforms with complete context over fragmented toolchains with tool-specific AI agents.
• Strong understanding of key personas including platform engineering leaders, DevOps directors, AI/ML leaders, and developers, and how they evaluate, purchase, and adopt AI solutions across different organizational AI maturity levels (evaluating AI, using AI coding tools, AI-first organizations).
• Experience working with large B2B enterprise customers navigating AI transformation, translating their challenges with fragmented trust, context, regulations, and budgets into clear positioning, differentiated messaging, and scalable go-to-market strategies.
• Track record of successfully launching new products, usage-based pricing models, or consumption-based offerings, including defining monetization strategy, coordinating partner ecosystem activities, and measuring business impact through pipeline generation, usage metrics, and revenue growth.
• Ability to synthesize qualitative feedback, product usage data, win/loss analysis, and market research into clear, actionable messaging frameworks, pricing recommendations, consumption model optimization, and revenue plays that address both technical and business buyer needs.
• Strong written and verbal communication skills, with ability to explain complex AI concepts (agentic workflows, unified data models, intelligent orchestration, MCP integration) to both technical and non-technical audiences through presentations, content, and enablement materials.
• Familiarity with AI coding tools landscape and ability to position GitLab's team-level orchestration across the complete software lifecycle.
• Strategic thinking about market opportunities in AI for software teams, competitive positioning against both AI coding tools and DevOps platforms, and business model innovation around usage-based pricing that demonstrates clear customer value.
• Proven experience being self-directed and working with minimal supervision, able to coordinate across many teams and lead cross-functional initiatives.
• Data-driven approach, using data to measure results, inform decision-making, and develop strategy.
• Openness to learning, with transferable skills from related areas such as MLOps, platform engineering, or developer experience, and a self-directed approach to staying current on AI industry trends, agentic AI developments, and enterprise AI adoption patterns.

About the team

The Core Platform Product Marketing team leads how we position and grow GitLab's intelligent orchestration capabilities and Duo Agent Platform. You'll join a highly collaborative group of experienced product marketers who share context, support each other's launches, and turn customer and market insights into clearer storytelling around the AI modernization journey. As a Lead Product Marketing Manager, AI, you'll operate as a senior contributor within this team, partnering with other Product Marketing Managers, driving monetization strategy for usage-based AI offerings, and helping to shape how we bring agentic workflows and team-agent collaboration to market. We believe the best AI marketing comes from people who are themselves AI-native practitioners.

You'll work with peers who focus on different parts of the platform (DevOps, Security) to share best practices, coordinate priorities around the three modernization journeys (DevOps, Security, AI), and learn from each other's launches. As a team, we're focused on improving how we support sales and customer-facing teams, measure the impact of AI investments, demonstrate ROI through usage metrics and cost savings, and continuously refine how we collaborate to position GitLab as the intelligent orchestration platform where teams stay in flow with their AI agents and ship software faster.

Narvar is growing! We are hiring a Senior Software Engineer II to build new products and improve all aspects of the Narvar platform. Data is at the core of our competitive advantage so the work you do has a large impact across the company, our business partners, and the lives of our end users.

Machine Learning Engineers at Narvar work across the stack. We are ‘full-stack’ ML Engineers. This means that we write production-level code and own machine learning operations for our teams. 

Day-to-day

• Design and deploy machine learning algorithms for use cases spanning e-commerce, consumer trends, markets, logistics, and new products
• Work on real-world consumer data for natural language processing, image classification, time series analysis, outlier detection, user modeling, etc
• Work with large unstructured data
• Be at the intersection of mathematics, machine learning, business, and computer science and impact millions of users through your work
• Multiply the effect of your data science and data team members by building frameworks, tools, and methodologies that the entire team use 
• Provide thought leadership to a team through high quality write-ups, reviews, and a strong vision grounded in practical experience and a wider industry view

What we’re looking for

• Strong machine learning skills. 
• Fluency in Python, PyTorch, Tensorflow, Pandas, numpy, and machine learning packages
• Data Engineering skills and large data experience. You should have dealt with large amounts of data (TB) in a production setting, built world class data pipelines using cutting edge tools (e.g. Spark).
• 10+ years of hands-on experience shipping models to production, working on a variety of problem spaces (eg: user modeling, spam classification, prediction, clustering etc)
• MS in Computer Science, Statistics, Math, Science (physical or social), Engineering or similar quantitative and computation field plus 5+ years of industry experience
• Strong software engineering and coding skills with the ability to write production quality code
• Strong understanding of probability & statistics, machine learning, and algorithms
• Experience with SQL and NoSQL databases
• Experience working with Linux, shell scripting
• Previous startup experience strongly preferred

Bonus Points

• Experience implementing applications on Google Cloud Platform
• Experience with deep generative models or graph learning a plus.
• Tag your application with your solution to an active / recently concluded Kaggle competition, to get ahead of the list :)
• Experience leading a team of data and data scientists; Strong ability to multiply the effect of the team and the team members; excellent written communication; self-starter that can balance sophistication with practicality 

Why Narvar?

We're on a mission to simplify the everyday lives of consumers. Post-purchase is a critical phase of the customer journey. That's why we created Narvar - a platform focused on driving customer loyalty through seamless post-purchase experiences that allow retailers to retain, engage, and delight customers. If you've ever bought something online, there's a good chance you've used our platform!

From the hottest new direct-to-consumer companies to retail’s most renowned brands, Narvar works with GameStop, Neiman Marcus, Sonos, Nike, and 1300+ + other brands. With hubs in San Francisco, Atlanta, London, and Bangalore, we've served over 125 million consumers worldwide across 10+ billion interactions, 38 countries, and 55 languages.

Pioneering the post-purchase movement means navigating into the unknown. Our team thrives on this sense of adventure while nurturing a mindset of innovation. We're a home for big hearts and we leave our egos at the door. We work hard but we always make time to celebrate professional wins, baby showers, birthday parties, and everything in between.

We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

#LI-BB1

#LI-Remote

Method is a global design and engineering consultancy founded in 1999. We believe that innovation should be meaningful, beautiful and human. We craft practical, powerful digital experiences that improve lives and transform businesses. Our teams based in New York, Charlotte, Atlanta, London, Bengaluru, and remote work with a wide range of organizations in many industries, including Healthcare, Financial Services, Retail, Automotive, Aviation, and Professional Services.

Method is part of GlobalLogic, a digital product engineering company. GlobalLogic integrates experience design and complex engineering to help our clients imagine what’s possible and accelerate their transition into tomorrow’s digital businesses. GlobalLogic is a Hitachi Group Company.

We are seeking an experienced Principal Data Architect to join our Data & AI team. In this leadership role, you will help shape modern data and AI architecture strategies that enable organizations to achieve business outcomes through scalable, reliable, and secure data platforms. You will work closely with senior stakeholders, client teams, and engineering teams to define architectural direction, guide implementation approaches, and support the delivery of data-driven capabilities across analytics, AI, and operational use cases. You will exemplify Method culture and values by driving standards of excellence and mentoring and educating those who are accountable to you on projects or within the data engineering discipline. You will be reporting into the head of the Data & AI team. 

This role requires a strong blend of technical depth, architectural thinking, client engagement and team mentorship. You will be expected to navigate ambiguity, align business and technology priorities, and help teams deliver practical, high-quality solutions that support long-term value creation. In addition to shaping solution direction, you will play an important role in guiding and developing data engineering teams through coaching, knowledge sharing, and hands-on support.

Travel for team, client and sales meetings is required, typically up to 25%. This is a US-based position in the East Coast or Mid-Central time zone.

Job Responsibilities

• Lead complex data and AI platform initiatives, addressing architectural concerns while enabling delivery teams to meet defined standards, timelines, and budgets.
• Provide client-facing technical leadership on data architecture, data engineering, analytics platforms, and AI/ML infrastructure.
• Collaborate with enterprise architects and senior technology stakeholders to align on architectural decisions, trade-offs, and implementation approaches.
• Communicate architectural concepts clearly to both engineering teams and business stakeholders.
• Design architectures that bridge operational systems and analytical platforms, enabling data products, advanced analytics, and AI capabilities.
• Define and implement architectures for data governance, security, privacy, and regulatory compliance.
• Establish and integrate data quality frameworks, observability practices, and data reliability processes.
• Partner with sales and pre-sales teams to shape solution approaches, validate technical feasibility, and support proposals.
• Develop new value propositions and offerings for the data engineering at Method, create go to market strategies, test and refine the offerings during the sales pursuits.
• Grow and maintain the data engineering team. Provide career guidance and facilitate career development opportunities across Method. 
• Create an environment that brings together the best of various data disciplines with care for the uniqueness of each project. 
• Foster a culture of curiosity and learning, creating opportunities for employees to learn and grow into our future leaders.

Skills Required
Technical Skills

• 8+  years of experience in data engineering, with 3+ years in a technical leadership role. 
• Experience designing and implementing modern data architectures, including lakehouse, data mesh, and real-time data platforms, and evaluating technology trade-offs.
• Strong background in distributed systems and data-intensive applications.
• Experience building and operating large-scale data platforms, including data warehouses, streaming systems, and data lakes.
• Expertise in data modeling, data platform operations, observability, and reliability engineering for data systems.
• Proficiency with modern data and distributed technologies such as Spark, Kafka, Flink, Trino/Presto, Iceberg/Delta/Hudi, and distributed storage systems.
• Experience designing streaming and low-latency architectures and understanding their operational trade-offs.
• Experience designing and deploying AI/ML platforms, including feature stores, model training pipelines, and model serving systems.
• Familiarity with MLOps and ML productionization practices, including CI/CD, model monitoring, and governance.
• Strong experience working with cloud platforms (AWS, Azure, or GCP) and cloud-native data services.
• Experience with modern data platforms such as Snowflake, Databricks, or similar analytics environments.
• Understanding of data governance frameworks, data cataloging, lineage, and privacy controls.
• Experience implementing data-driven decision systems, advanced analytics, and machine learning solutions in enterprise environments.

Professional Skills

• Advise C-suite executives on data strategy, AI investment, and digital transformation at the highest organizational level.
• Strong experience supporting pre-sales, solution shaping, and technical discovery engagements.
• Support client partners in growing key accounts by identifying new opportunities, navigating complex situations, and educating clients on the value of our work beyond data and AI.
• Excellent stakeholder management skills and the ability to build trust with both business and technical leaders.
• Ability to cultivate strong partnerships across organizations to drive adoption of modern data and AI capabilities.
• Strong influencing skills, with the ability to galvanize, inspire, and align others around a shared direction.
• Contribute Thought Leadership through presentations, blogs, or public talks
• Strong conflict resolution and risk management skills.
• Team player with the capacity to mentor, guide, and champion engineering teams and architects.
• Commitment to technical excellence, pragmatic delivery, and continuous improvement. 

Why Method?

We look for individuals who are smart, kind and brave. Curious people with a natural ability to think on their feet, learn fast, and develop points-of-view for a constantly changing world find Method an exciting place to work. Our employees are excited to collaborate with dispersed and diverse teams that bring together the best in thinking and making. We champion the ability to listen, and believe that critique and dissonance lead to better outcomes. We believe everyone has the capacity to lead and look for proactive individuals who can take and give direction, lead by example, enjoy the making as much as they do the thinking, especially at senior and leadership levels.

We believe in work/life balance. Seriously. We offer a ton of competitive perks, including:

• Continuing education opportunities 
• Flexible PTO and work-from-home policies 
• Pension 
• Health and dental benefits
• Company lunches, company outings, along with a lot of snacks 
• Health and wellness programs 
• Other location specific perks (just ask!)

Next Steps

If Method sounds like the place for you, please submit an application. Also, let us know if you have a presence online with a portfolio, GitHub, Dribbble or other platform.

* For information on how we process your personal data please see Privacy.

* If you are a California resident, more details on how we process your personal information can be found in the CCPA Recruitment Privacy Notice (https://www.globallogic.com/privacy/ccpa-recruitment-privacy-notice/)"

Colorado Applicants (Colorado Equal Pay for Equal Work Act Disclosure):  The starting salary range for this role to be performed in Colorado is estimated to be between $160,000 to $200,000 annually.  This salary range is specific to Colorado residents only, and provided as a general estimate.  The amount offered may be higher or lower. Method  takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations. 

New York City Applicants (New York City Local Law 32;  Pay Transparency Law):  The starting salary range for this role to be performed in New York City is from $192,000 to $205,000. This salary range is specific to New York City residents only, and provided as a general, good faith estimate. The amount offered may be higher or lower. Method takes many factors into making an offer, including candidate qualifications, work experience, operational needs, travel and onsite requirements, internal peer equity, prevailing wage, responsibilities, and other market and business considerations.

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Team Lead, GenAI Engineering who will champion and guide a team of Software Developers and Data Scientists, accounting for the end-to-end implementation and deployment of advanced Generative AI solutions. The projects will vary in scope, complexity, and affected business area. If you love technology, and are keen to join an industry leader — we would love to hear from you!

What you'll do:

As a Team Lead, GenAI Engineering, your key area of responsibility will be leading the design, development, and deployment of cutting-edge Generative AI software applications, establishing high technical standards through code reviews and scalable architectures, and ensuring all data products meet critical business needs. You will need to work closely with the Manager of AI Engineering, Geotab’s software engineering and data science squads, and cross-functional stakeholders to translate complex technical insights into actionable reports.

To be successful in this role you will be a technical leader with an entrepreneurial mindset who is comfortable in a dynamic environment and possesses a passion for coaching and mentoring team members toward their full potential. In addition, the successful candidate will have strong analytical and problem-solving skills, with the ability to manage multiple development projects simultaneously, break down complex requirements into executable tasks, and make data-driven decisions to ensure timely, high-standard results.

How you'll make an impact:

• Cultivate a High-Performing Team: Actively mentor and coach team members on best practices in both AI product development and software engineering. Beyond technical guidance, serve as a career coach, conducting regular 1-on-1s to align individual aspirations with organizational goals and providing the radical candor necessary for continuous professional growth.
• Own the Hiring Process: Drive the end-to-end recruitment of top-tier talent, rigorously assessing technical depth (Data Science and LLM Engineering) and cultural alignment. Design and oversee a seamless onboarding experience that integrates new hires into the GenAI stack and team culture with speed and clarity.
• Foster a Culture of Innovation: Encourage and enable the team to experiment with new technologies and methodologies, making pragmatic trade-offs to meet project goals while fostering a culture of continuous learning.
• Performance Management & Accountability: Establish clear performance metrics and KPIs for the engineering squad. Take ownership of the performance review cycle, identifying high-potential talent for advancement and proactively managing underperformance through structured support and feedback loops.
• Spearhead Advanced GenAI Development: Lead the design, development, and deployment of cutting-edge Generative AI software applications. Research and implement novel solutions using techniques such as prompt engineering, Agentic workflows, and Retrieval Augmented Generation (RAG) to solve complex business challenges.
• Technical Direction & Code Quality: Establish and maintain a high technical bar for the team. Perform regular code reviews, ensure adherence to software engineering best practices, and lead the design of objective evaluation systems to rigorously assess model quality, performance, and user experience.
• Architect Scalable Solutions: Oversee the design and maintenance of high-quality, scalable, and secure AI architectures on cloud platforms. Ensure the architectural integrity of applications built on top of Generative AI models, balancing critical considerations like AI safety, latency, and cost.
• Task Management & Delivery: Serve as the primary technical subject matter expert. Break down complex, high-level requirements into executable technical tasks and sprints. Own the planning, execution, and delivery of multiple development projects, ensuring they are completed on time and to a high standard.
• Lead Communication and Documentation: Act as the primary technical point of contact. Manage communication with cross-functional stakeholders, translating complex technical insights into clear, actionable reports. Ensure comprehensive documentation of research, methodologies, and system designs is maintained.

What you'll bring to the role:

Why job seekers choose Geotab:

This is Engineering at Lattice

Lattice’s Engineering team is continuously improving both our product and our craft. We build maintainable, performant systems using modern technologies, and we collaborate closely with product and design to deliver exceptional user experiences.

Our AI Engineering team is building the systems that power how AI works across Lattice. We’ve laid the foundations: traces are flowing and evals are running - and we’re now focused on defining how our AI products are measured, improved, and trusted at scale. This is a high-ownership role where you’ll help shape evaluation methodology, agent architecture, and the core systems that determine how AI performs in production.

What You Will Do

Evaluation Infrastructure

• Design and ship a robust, end-to-end AI evaluation framework, covering offline evals, production tracing, and human-in-the-loop feedback loops, connected across all of Lattice’s AI use cases.
• Define and instrument the metrics that actually matter: agent task completion, hallucination rates, response quality, user engagement, and downstream business outcomes.
• Build and maintain evaluation datasets, test harnesses, and automated scoring pipelines to catch regressions before they ship.
• Identify and surface the drivers of agent quality improvement, giving the team clear signals on where to invest.

Agent Architecture & Infrastructure

• Architect and implement reusable agent infrastructure: multi-turn conversation workflows, recommendation services, LLM DAGs, and standardized agent topology patterns using LangGraph.
• Build and scale RAG pipelines and retrieval infrastructure, including vector store management and retrieval quality optimization.
• Make principled build vs. buy decisions across LLM providers, agent frameworks, and evaluation tooling, balancing capability, cost, latency, and vendor risk.
• Contribute to production AI systems with a strong focus on reliability, observability, and performance, not just prototypes.

Technical Leadership & Collaboration

• Own projects end-to-end: scope them, drive them to completion, and bring in the right people at the right time.
• Partner with engineering leads and managers to inform technical direction on agent quality and evaluation strategy you’ll be expected to hold intelligent, substantive conversations about methodology, not just implementation.
• Raise the AI engineering bar across the broader team through code review, documentation, and thoughtful technical debate.

What You Will Bring to the Table

Experience

• 5+ years of professional software engineering experience with significant time spent on production AI/ML systems.
• Deep hands-on experience with LLM-based systems: prompt engineering, RAG pipelines, agent orchestration, evaluation metrics, and model fine-tuning.
• Proven ability to work with data and understand statistics, especially in experiments.
• Proven ability to build and operate agentic AI systems in production: multi-step workflows, multi-agent topologies, and the failure modes that come with them.
• Strong command of AI evaluation: you’ve built eval frameworks before, you know the difference between a good eval and a vanity metric, and you have opinions about it.
• Production-grade Python engineering: clean, maintainable, testable code.

Technical Skills

• LangGraph or comparable agent orchestration frameworks. You’ve built real agent workflows with it, not just tutorials.
• LangSmith or comparable LLM observability tooling for tracing, evaluation, and debugging.
• Reads AI papers & blogs regularly and is a trusted source of AI trends.
• Vector databases (Pinecone or similar) and retrieval system design.
• AWS ecosystem or other cloud infrastructure (ex GCP). Comfortable with lambdas, queues, and cloud-native architecture.
• Familiarity with TypeScript is a plus. Our full-stack engineers use it and cross-pollination is valuable.

Ways of Working

• Clear eyes: you see problems as they are, not as you’d like them to be. You surface hard truths early and address them directly.
• Ship, shipmate, self: you prioritize the product and your teammates. Low ego, high ownership.
• You’re as comfortable in ambiguity as you are in well-defined problems: early foundations mean you’ll encounter both.
• Strong technical communication: you can debate evaluation methodology with an AI lead and explain it clearly to an EM in the same afternoon.

Nice to Have

• Experience with RLHF, LoRA, or other model adaptation techniques.
• Background in traditional ML (supervised/unsupervised, neural networks) and knowing when an LLM is overkill.
• Experience with MLOps tooling: MLflow, DataDog, CI/CD pipelines for model deployment.
• Published work, conference talks, or open-source contributions in AI/ML.
• Experience in HR tech, people analytics, or other domains where data quality and trust are critical.

Location Requirement:
This role is open to candidates located in British Columbia or Ontario, Canada. At this time, we are only able to hire employees residing in these provinces.

The estimated annual cash salary for this role is CAD $123,750 - CAD $165,000. This position is also eligible for stock options, subject to the terms of Lattice’s applicable plans.

Benefits: The Company offers the following benefits for this position, subject to applicable eligibility requirements: Medical insurance; Dental insurance; Life, AD&D, and Disability Insurance; Natural Disaster Support Program; Wellness Apps; Paid Parental Leave, Paid Time off inclusive of holidays and sick time; Working Remotely Stipend; One time WFH Office Set-Up Stipend; Retirement Plan; Financial Planning; and Learning & Development Budget.

Note on Pay Transparency:
Lattice provides an estimate of the compensation for roles that may be hired as required by regulations. Compensation may vary based on (a) location, as Lattice factors in specific location when benchmarking compensation for most roles; (b) individual candidate skills and qualifications; and (c) individual candidate experience. Additionally, Lattice leverages current market data to determine compensation, so posted compensation figures are subject to change as new market data becomes available. The salary, other compensation, and benefits information is accurate as of the date of this posting. Lattice reserves the right to modify this information at any time, subject to applicable law.

Lattice welcomes and encourages applications from people with disabilities. Accommodations are available on request for candidates taking part in all aspects of the recruitment and selection process.

#LI-Remote

Note: This isn’t an active role right now, but we’re building a community of great talent for future opportunities at Caylent. If your background aligns with what we’re looking for, our team may reach out to learn more about you and explore potential future fits.

The Mission

We are seeking an exceptional Machine Learning Architect to join our growing Cloud Native Applications team. The right candidate is someone who has deep expertise in ML system design and is passionate about working with our customers, partners, and colleagues to drive innovation forward. Your mission will be to work alongside Caylent’s Engineers, Engineering Managers, and Project Managers to deliver AWS solutions across our diverse and forward-thinking customer base. You’ll work with the latest technologies and support customers looking to bring cutting-edge ideas to market.

Your Assignment

• You will be a mission control specialist, guiding Cayliens and Customers alike through Agile ceremonies like stand-ups, retrospectives, and more.
• You will translate customer requirements and into a workable backlog of tickets for engineers.
• Delegate tickets to a team of engineers in order to complete customer projects.
• Lead requirements gathering, backlog grooming, and architecture discussions.
• Apply your understanding of DevOps pipelines, including build automation, branching strategies, CI/CD, Infrastructure as Code, security, monitoring, logging, and alerting.
• Troubleshoot and resolve issues in customer dev, test, and production environments.
• Automate software testing at multiple levels (component, configuration item, subsystem, system) and monitor results.
• Write production quality code, including unit and integration tests. 
• Work with a team to deliver top-quality cloud native applications on AWS for customers.
• Clearly communicate and document your designs, processes, and procedures.
• You will demonstrate a passion to Stay Curious as you mentor peers, tackle new technologies, and learn from our word-class team of engineers.
• Coach and mentor less experienced teammates, coach and be mentored by world class engineers.

Your Qualifications

Core Consulting Qualifications 

Customer Experience 

• Confidently addresses client questions and identifies gaps in requirements with  proposed next steps. 
• Focus on delivering clear, actionable solutions that meet client goals

Collaboration 

• Facilitates alignment across stakeholders or technical priorities and deliverables.
• Navigates differing perspectives with professionalism to ensure shared understanding  and progress. 

Communication 

• Breaks down complex technical concepts for non-technical audiences in a clear, concise  manner. 
• Adapts communication style based on audience and context to improve clarity and decision-making. 

Technical Qualifications

• Experience with IaC tools (CloudFormation, CDK, Terraform).
• Expert level experience in Amazon SageMaker and ML libraries (TensorFlow, MXNet, PyTorch, Scikit-learn).
• Strong understanding of ML concepts: feature engineering, hyperparameter tuning, optimization strategies.
• Familiarity with MLOps tools (MLflow, Neptune, Comet).

Benefits 

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Base Salary Range: The expected base salary range for this position is CAD $152,000 - $171,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

This role may require up to 25% travel, depending on business needs. 

We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca, AutoSync, Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence. 

Learn more at tradercorporation.com. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. 

As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and machine learning systems that sit at the core of our marketplace platforms across Europe and Canada. 

You design, build, and operate machine learning and GenAI systems that run in production and matter to the business. You work on complex, ambiguous problems, exercise strong technical judgment, and take responsibility for outcomes - not just models. While this is a hands-on role, you are also expected to influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. This position is permanent and based in Toronto. 

What you’ll do 

• Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement 

• Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability 

• Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes 

• Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints 

• Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems 

What you’ll need  

• Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field 

• 5+ years of experience building and owning production ML systems end-to-end in a real-world environment 

• Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production 

• Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale 

• Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations 

• Ability to influence technical decisions through clear judgment and collaboration, not formal authority 

• Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback 

• Strong sense of ownership and accountability for outcomes, with a pragmatic approach to trade-offs and delivery 

What’s in it for you 

We understand that there is life at work and life outside of work. Here are a few benefits that support us to be our creative best.   

• Gym discounts 
• Employee and Family Assistance program 
• Virtual wellness events 
• Conferences & training budget 
• Regular internal training programs 
• Financial planning with 3% matching Pension  
• Competitive salary 
• Annual bonus structure 

The base salary range for this position is CAD $180k – $120k.

This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings. 

Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position.

Vacancy Status: This job posting is for an existing vacancy. 

At AutoScout24, we’re excited to be hiring for our Canadian company, Trader Corporation - a key part of our international family.

As the Canadian arm of Europe’s largest online car marketplace, Trader Corporation plays a vital role in transforming how people buy, sell, and finance vehicles. With well-known brands like AutoTrader.ca, AutoSync, and Dealertrack Canada, Trader Corporation is driving digital innovation in the automotive industry — now reaching over 25 million Canadians every month.

What You’ll Do 

• Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
• Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.
• Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination.
• Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns.
• Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.
• Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions. 

What you’ll bring: 

• A degree in computer science, data science, engineering, or a related field.
• Experience building agentic GenAI systems in production (e.g., LangChain, AutoGen, Atomic Agents, or similar frameworks).
• Strong coding skills in Python and experience with robust software engineering practices.
• Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.
• Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift).
• Experience deploying AI systems in a cloud environment and working with modern ML stacks.
• Familiarity with MLOps, prompt engineering, or LLM-based application design.
• Ability to explain complex AI topics in clear and actionable language to technical and non-technical stakeholders.
• High motivation, ownership mentality, and a strong drive to build impactful AI products.
• Fluency in English; German is a plus. 

The base salary range for this position for Canada is CAD 180K – CAD 200K.

This range reflects the expected compensation at the time of posting. The final offer may vary based on relevant skills, experience, location, and market conditions. Based on the role the total rewards package may also include benefits, bonus, and other employee offerings.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

Note: Benefits may vary by location and are subject to local regulations.

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Vancouver_Canada

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution. While this role is remote, it may require in-person participation. You will be encouraged to attend company events throughout the year. These events will take place at a designated SurveyMonkey office or location.

#LI-remote

What we’re looking for

This is a highly visible, strategic, and impactful role, reporting the VP of Engineering for SurveyMonkey Core Engineering. As the Senior Director of AI, you will be a critical leader in defining the future of SurveyMonkey's products and services. You will not just manage the Machine Learning and Data Science teams, but help drive the fundamental shift in how our customers gather, analyze, and act on feedback. This requires both strong strategic thinking, and solid experience building models and deploying AI/ML systems end-to-end (from data to production). The successful candidate will make a material contribution to the company's success by providing thought leadership around how to leverage AI technology in the SurveyMonkey product in an intuitive and natural way.

What you’ll be working on

Strategic Leadership & Product Alignment

• Strategic Roadmapping: Define and execute the long-term data science strategy, ensuring alignment with SurveyMonkey’s overarching business objectives and product vision.
• Product-to-Data Science Translation: Act as the primary liaison between Product Management and the Data Science team, expertly mapping ambitious SurveyMonkey product requirements (e.g., automated thematic analysis, predictive modeling, intelligent survey generation) into clear, technically feasible data science projects.
• AI-First Transformation: Support the charge in migrating SurveyMonkey from a traditional SaaS product to an AI-first platform, embedding advanced data science and LLM capabilities deeply within the product experience.

Technical Expertise & Innovation

• LLM and NLP Integration: Drive the strategy for integrating and leveraging Large Language Models (LLMs) and advanced Natural Language Processing (NLP) techniques to enhance our text analytics, sentiment analysis, and generative features within the product.
• Familiarity with MLOps / LLMOps practices: Experience developing and deploying a Machine Learning Platform.  Experience with Agentic AI Architecture, deployment and execution. Familiarity with modern MLOps tools and platforms (e.g., AWS SageMaker, GCP Vertex AI, MLflow).
• Technical Direction: Set the technical standards for model development, deployment, monitoring, and maintenance. Ensure the team utilizes best-in-class data science models, tools, and platforms for scalable production systems.
• Ownership of model lifecycle: experimentation → deployment → monitoring → iteration
• Stay Current: Actively research, evaluate, and evangelize the latest developments in machine learning, deep learning, MLOps, and data science methodologies, ensuring the team's capabilities remain cutting-edge.

Team Management & Development

• Management and Motivation: Lead, mentor, and inspire a high-performing team of data scientists and machine learning engineers. Foster a culture of innovation, rigor, collaboration, and continuous learning.
• Recruitment and Growth: Recruit top-tier data science talent, manage performance, and define career progression paths to ensure the ongoing growth and retention of team members.

We’d love to hear from people with

• Experience: 10+ years of progressive experience in data science, including significant experience with AI/ML platforms, and at least 5 years in a Director level leadership role managing and scaling data science or machine learning teams in a commercial software environment.
• Experience building or leading AI/ML platforms: (feature stores, model serving, training pipelines) in a Cloud Environment like AWS
• Deep Technical Acumen: Extensive practical experience with and deep theoretical understanding of machine learning algorithms, statistical modeling, and experimental design (A/B testing).
• NLP and LLM Proficiency (Critical): Demonstrated experience in applying, fine-tuning, and integrating Large Language Models (LLMs) and advanced Natural Language Processing techniques into production systems, especially for tasks related to text classification, summarization, and generation.
• Product Thinking: Exceptional ability to translate ambiguous or high-level product needs into concrete, defensible data science problems and solutions.
• Communication: Excellent written and verbal communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders (e.g., Executives, Product Managers, Marketing).
• Education: Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.

The base pay provided for this position ranges from CAD $224,000/ year - $336,000/ year depending on the geographic market and assuming a full-time schedule. Actual base pay is based on a number of factors including market location, job-related knowledge, education or training, skills, and experience.

Bonuses may also be offered as part of the total compensation package, in addition to a competitive benefits package including medical, dental, vision, life, and disability insurance; RRSP matching; flexible spending & health savings account; paid holidays; paid time off; employee assistance program; and other company benefits. 

This opening is for an existing vacancy.

SurveyMonkey believes in-person collaboration is valuable for building relationships, fostering community, and enhancing our speed and execution in problem-solving and decision-making. As such, you will be required to work from our Ottawa office up to 1 day per week.

#LI-Hybrid

About the Company 

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.

A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. 

Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer. 

Meet the Team: 

As a Staff Machine Learning Engineer specializing in BEV (Bird’s-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. 

You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc’s autonomous driving stack. 

This is a technical leadership role focused on model innovation and maturity, not downstream feature integration. 

What You’ll Do 

• Lead BEV model development: Define and execute the technical roadmap for BEV-based perception models across multiple tasks (e.g., detection, segmentation, road topology, and scene understanding). 
• Design advanced multi-modal architectures that fuse heterogeneous sensor data (camera, LiDAR, radar, HD maps) into unified spatial representations.
• Develop foundational perception models leveraging BEV transformers, voxel-based encoders, or implicit scene representations.
• Own large-scale training workflows — from data sampling strategies and augmentation pipelines to distributed training and hyperparameter optimization.
• Advance model robustness and generalization, addressing long-tail conditions such as low visibility, occlusions, and rare scene configurations.
• Establish evaluation frameworks for geometric accuracy, temporal stability, and cross-domain transfer performance.
• Collaborate cross-functionally with sensor calibration, mapping, and fusion teams to ensure cohesive perception model interfaces.
• Mentor and guide ML engineers, cultivating best practices in experimentation, code quality, and model validation.
• Stay at the forefront of ML research, exploring self-supervised learning, large-scale pretraining, or foundation models for 3D perception. 

What You’ll Need to Succeed 

• 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems
• M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience).
• Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion.
• Strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data.
• Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
• Experience with large-scale data pipelines, distributed training, and experiment management systems.
• Demonstrated leadership in driving ML model innovation and mentoring technical teams. 

Bonus Points! 

• Experience with autonomous driving or robotics perception in production environments.
• Experience with MLOps and infrastructure tools (Ray)
• Hands-on expertise in BEV-based ML architectures, LiDAR-vision fusion, or spatial-temporal modeling.
• Familiarity with 3D labeling, calibration, and sensor simulation pipelines.
• Track record of publications or open-source contributions in top-tier venues (CVPR, ICCV, NeurIPS, ICRA, CoRL).
• Understanding of performance tradeoffs and deployment constraints (latency, memory, accuracy). 

Knowledge of English is required since the selected candidate will need to collaborate daily with English-speaking colleagues in the United States and work with technical documentation written exclusively in English. 

Work Location: For this position, we are open to hiring in either the Torc Montreal, Quebec (Canada) or Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States or Canada.

Perks of Being a Full-time Torc’r (Canada) 

Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers: 

• A competitive compensation package that includes a bonus component and stock options
• Medical, dental, and vision for full-time employees
• RRSP plan with a 4% employer match
• Public Transit Subsidy (Montreal area only)
• Flexibility in schedule and generous paid vacation
• Company-wide holiday office closures
• Life Insurance 

 At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities. Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply. 

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. 

CAD Compensation Range: $209,300-313,800 CAD

Job ID: 102405

À propos de l’entreprise  

À Torc, nous avons toujours cru que la technologie des véhicules autonomes transformera la façon dont nous voyageons, transportons la marchandise et faisons des affaires.  

Leader de la conduite autonome depuis 2007, Torc a passé plus d’une décennie à commercialiser des solutions aux côtés de partenaires chevronnés. Nous faisons maintenant partie de la famille Daimler, ce qui nous permet de nous concentrer uniquement sur le développement de logiciels pour les camions automatisés. Nous transformerons la façon dont le monde transporte la marchandise.  

Joignez-vous à notre équipe : catapultez votre carrière au sein de l’entreprise ayant contribué à créer la technologie de conduite autonome (CA). Nous sommes la première entreprise de logiciels de CA ayant eu la vision de faire équipe directement avec un constructeur de camions.  

Rencontrez l’équipe : 

En tant qu’ingénieur(e) “Staff" en apprentissage automatique spécialisé(e) dans le BEV (Bird’s-Eye View) et la Perception multimodale, vous dirigerez le développement de modèles de nouvelle génération qui unifient les informations provenant des caméras, du LiDAR et du radar pour offrir une riche compréhension spatiale de l’environnement de conduite. 

Vous conduirez l’innovation architecturale, la formation de modèles à grande échelle et les améliorations basées sur les données qui font directement progresser les capacités de perception au cœur de la pile de conduite autonome de Torc. 

Il s’agit d’un rôle de leadership technique axé sur l’innovation et la maturité du modèle, et non sur l’intégration des fonctionnalités en aval. 

Ce que vous ferez 

• Diriger le développement du modèle BEV : Définir et exécuter la feuille de route technique pour les modèles de perception basés sur le BEV à travers de multiples tâches (par exemple, la détection, la segmentation, la topologie de la route et la compréhension de la scène). 
• Concevoir des architectures multimodales avancées qui fusionnent des données de capteurs hétérogènes (caméra, LiDAR, radar, cartes HD) en représentations spatiales unifiées.
• Développer des modèles de perception fondamentaux en s’appuyant sur les transformateurs BEV, les encodeurs basés sur les voxels ou les représentations implicites de la scène.
• Possède des flux de travail de formation à grande échelle, depuis des stratégies d’échantillonnage de données et des pipelines d’augmentation jusqu’à la formation distribuée et à l’optimisation des hyperparamètres.
• Améliorer la robustesse et la généralisation du modèle, en tenant compte des conditions de longue traîne, telles que la faible visibilité, les occlusions et les configurations rares de la scène.
• Établir des cadres d’évaluation pour la précision géométrique, la stabilité temporelle et les performances de transfert entre domaines.
• Collaborer de manière transversale avec les équipes chargées de l’étalonnage des capteurs, de la cartographie et de la fusion afin d’assurer la cohésion des interfaces des modèles de perception.
• Encadrer et guider les ingénieurs en apprentissage automatique, en cultivant les meilleures pratiques en matière d’expérimentation, de qualité du code et de validation des modèles.
• Reste à la pointe de la recherche en apprentissage automatique, en explorant l’apprentissage autosupervisé, le préentraînement à grande échelle, ou les modèles de base pour la perception 3D. 

Ce dont vous aurez besoin pour réussir : 

• Maîtrise ou doctorat en informatique, génie électrique, robotique ou autre domaine connexe (ou expérience pratique équivalente).
• 10 ans d’expérience et plus en apprentissage approfondi pour la perception, la vision 3D, ou les systèmes autonomes.
• Expertise avérée dans la modélisation BEV, la compréhension des scènes 3D et la fusion multivue.
• Solide expérience en fusion de capteurs multimodaux, en particulier l’intégration de données d’appareils photo et de LiDAR.
• Maîtrise de Python et des Cadres d’applications d’apprentissage approfondi, tels que PyTorch ou TensorFlow.
• Expérience des pipelines de données à grande échelle, de la formation distribuée et des systèmes de gestion des expériences.
• Leadership avéré dans la conduite de l’innovation en matière de modèles d’apprentissage automatique et dans le mentorat d’équipes techniques. 

Points bonus! 

• Expérience de la conduite autonome ou de la perception robotique dans des environnements de production.
• Expérience des outils MLOps et d’infrastructure (Ray)
• Expertise pratique dans les architectures d’apprentissage automatique basées sur le BEV, la fusion LiDAR-vision ou la modélisation spatio-temporelle.
• Familiarité avec l’étiquetage 3D, l’étalonnage et les pipelines de simulation de capteurs.
• Expérience de publications ou de contributions à des logiciels libres dans des domaines de premier plan (CVPR, ICCV, NeurIPS, ICRA, CoRL).
• Compréhension des compromis de performance et des contraintes de déploiement (latence, mémoire, précision). 

La connaissance de l’anglais est exigée puisque la personne retenue devra collaborer de façon journalière avec des collègues anglophones aux États-Unis et travailler avec la documentation technique rédigée uniquement en anglais. 

Avantages d’être un employé à temps plein Torc’r 

Torc se soucie de ses membres d'équipe et s'efforce de fournir des avantages et des ressources pour soutenir leur santé, leur équilibre entre vie professionnelle et vie personnelle, ainsi que leur avenir. Notre culture est collaborative, dynamique et axée sur le travail d'équipe. Torc offre: 

• Un programme de rémunération concurrentiel incluant un volet de primes et des options d’achat d’actions
• Une couverture médicale, dentaire et de la vue pour les employés à temps plein
• Un régime d’épargne-retraite (REER) avec une contribution de l’employeur de 4 %
• Une subvention pour le transport en commun (uniquement dans la région de Montréal)
• Une flexibilité des horaires et des vacances payées généreuses
• Des fermetures de bureau pendant les congés fériés à l’échelle de l’entreprise
• Une assurance-vie 

Notre rémunération reflète le coût de la main-d'œuvre sur plusieurs marchés géographiques. Le salaire est déterminé en fonction d'un certain nombre de facteurs et peut varier en fonction des connaissances, des compétences et de l'expérience liées au poste. Le programme de rémunération globale de Torc comprend également notre prime corporative et notre régime d’options d’achat d’actions.  Selon le poste proposé, des primes d’embauche, des indemnités de relocalisation ou d’autres formes de rémunération peuvent aussi être inclus dans le cadre du programme de rémunération globale, en plus d’une gamme complète d’avantages sociaux, médicaux, financiers et/ou autres. 

À Torc, nous nous engageons à cultiver un milieu de travail diversifié et inclusif. Nous célébrons l’unicité de chaque membre de l’équipe de Torc. Nous ne faisons pas de discrimination par rapport à l’origine ethnique, la religion, la couleur de peau, la nationalité, le genre (y compris la grossesse, les enfants ou autre condition médicale), l’orientation sexuelle, l’identité de genre, l’expression de genre, l’âge, le statut de vétéran ou les handicaps. 

Même si vous ne répondez pas à 100 % des qualifications énumérées pour ce poste, nous vous invitons à postuler. 

Numéro de poste: 102405

Fourchette salariale pour le poste Fourchette de rémunération au Canada:

$209,200 - $313,800 CAD

MaintainX is the world’s leading mobile-first Asset and Work Intelligence platform for industrial and frontline environments. We’re a modern, IoT-enabled, cloud-based solution that powers maintenance, safety, and operations on physical equipment and facilities.

We help 12,000+ organizations—including Duracell, Univar Solutions, Titan America, McDonald’s, Brenntag, Cintas, Xylem, and Shell—achieve operational excellence and reliability at scale.

Following our $150 million Series D led by Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures, and Ridge Ventures, MaintainX has raised a total of $254 million, valuing the company at $2.5 billion.

As we enter our next phase of growth, we’re investing deeply in AI/ML, LLMs, and Industrial IoT to transform how frontline teams operate—predicting failures before they happen, automating workflows, and embedding intelligence into every asset and procedure.

The Role

We are seeking a highly skilled and motivated Senior Applied Machine Learning Developer to guide the technical direction and architecture of our Predictive Maintenance and Asset Intelligence initiatives.

You’ll combine deep ML expertise with strong software development and leadership skills—mentoring developers, scaling systems, and driving the roadmap for AI-enabled maintenance intelligence across thousands of industrial sites.

This role sits at the intersection of ML architecture, IoT data systems, and product impact, shaping the foundation for MaintainX’s predictive and generative AI strategy.

What you’ll do:

• Lead technical direction for predictive maintenance, anomaly detection, and LLM-powered intelligence across MaintainX products.
• Architect end-to-end ML systems—from data ingestion and feature development to model training, deployment, and monitoring.
• Mentor a growing team of ML and data developers, instilling best practices for experimentation, evaluation, and model lifecycle management.
• Partner with product and software development leaders to align AI roadmap with customer needs and business goals.
• Design reliable data and feedback loops that connect customer telemetry and operator feedback to model retraining.
• Drive performance optimization through techniques like quantization, distillation, and scalable inference serving.
• Work with LLM frameworks (LangChain, LlamaIndex, Hugging Face) to build reasoning systems and agentic workflows for asset and work intelligence.
• Ensure ML infrastructure meets production standards for latency, reliability, explainability, and security.

About you:

• 7+ years of experience in Machine Learning, Data Science, or Applied AI.
• Expertise in Python, and strong familiarity with PyTorch, TensorFlow, and cloud ML stacks (AWS, Databricks, or similar).
• Proven experience deploying production ML systems—not just prototypes—at scale.
• Strong background in LLMs, time-series modeling, and anomaly detection for real-world data.
• Demonstrated ability to lead architectural decisions, mentor developers, and collaborate across product, data, and platform teams.
• Knowledge of MLOps tooling (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field preferred.

Bonus skills: 

• Experience with OCR for extracting structured data from documents.
• Background in time-series modeling for predictive maintenance and anomaly detection.
• Familiarity with Industrial IoT systems (sensors, telemetry, edge computing).
• Experience applying reinforcement learning or agentic architectures for decision-making and control systems.
• Contributions to open-source ML frameworks or research in reliability, explainability, or digital twins.

What’s in it for you:

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A high impact Culture:
• You’ll work with Smart, Humble Optimists across the globe.
• Meritocratic environment where ideas and outcomes are publicly celebrated.

About us:

We exist to make the lives of frontline and maintenance teams easier by building software that meets their real-world needs. Our product transforms how 80% of the global workforce—those who don’t sit behind a desk—manage their operations, assets, and teams.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

MaintainX est la première plateforme mobile au monde dédiée à la gestion des actifs et des tâches dans les environnements industriels et de première ligne. Nous proposons une solution moderne, basée sur l'IoT et le cloud, qui facilite la maintenance, la sécurité et l'exploitation des équipements et installations physiques.

Nous aidons plus de 12 000 organisations, dont Duracell, Univar Solutions, Titan America, McDonald's, Brenntag, Cintas, Xylem et Shell, à atteindre l'excellence opérationnelle et la fiabilité à grande échelle.

À la suite de notre série D de 150 millions de dollars menée par Bain Capital Ventures, Bessemer Ventures, August Capital, Amity Ventures et Ridge Ventures, MaintainX a levé un total de 254 millions de dollars, valorisant la société à 2,5 milliards de dollars.

Alors que nous entrons dans notre prochaine phase de croissance, nous investissons massivement dans l'IA/ML, les LLM et l'IoT industriel afin de transformer le mode de fonctionnement des équipes de première ligne, en prédisant les pannes avant qu'elles ne se produisent, en automatisant les flux de travail et en intégrant l'intelligence dans chaque actif et chaque procédure.

Le poste

Nous recherchons un développeur(se) senior en apprentissage automatique appliqué hautement qualifié et motivé pour orienter la direction technique et l'architecture de nos initiatives en matière de maintenance prédictive et d'intelligence des actifs.

Vous combinerez une expertise approfondie en apprentissage automatique avec de solides compétences en génie logiciel et en sens du leadership. Vous encadrerez des ingénieurs, développerez des systèmes et piloterez la feuille de route pour l'intelligence de maintenance basée sur l'IA sur des milliers de sites industriels.

Ce poste se situe à la croisée de l'architecture d'apprentissage automatique, des systèmes de données IoT et de l'impact des produits, et constitue le fondement de la stratégie d'IA prédictive et générative de MaintainX.

Ce que vous ferez:

• Diriger la direction technique pour la maintenance prédictive, la détection des anomalies et l'intelligence alimentée par LLM dans tous les produits MaintainX.
• Concevoir des systèmes ML de bout en bout, de l'ingestion des données et le développement des fonctionnalités à la formation, au déploiement et à la surveillance des modèles.
• Encadrer une équipe croissante de développeurs(ses) ML et de données, en inculquant les meilleures pratiques en matière d'expérimentation, d'évaluation et de gestion du cycle de vie des modèles.
• Collaborer avec les responsables des produits et de développement afin d'aligner la feuille de route de l'IA sur les besoins des clients et les objectifs commerciaux.
• Concevoir des boucles de données et de rétroaction fiables qui relient la télémétrie des clients et les commentaires des opérateurs au réentraînement des modèles.
• Optimiser les performances grâce à des techniques telles que la quantification, la distillation et le service d'inférence évolutif.
• Travailler avec des cadriciels LLM (LangChain, LlamaIndex, Hugging Face) pour créer des systèmes de raisonnement et des flux de travail agentifs pour l'intelligence des actifs et du travail.
• S'assurer que l'infrastructure ML répond aux normes de production en matière de latence, de fiabilité, d'explicabilité et de sécurité.

À propos de vous:

• Plus de 7 ans d'expérience dans le domaine de l'apprentissage automatique, de la science des données ou de l'IA appliquée.
• Expertise en Python et excellente maîtrise de PyTorch, TensorFlow et des piles ML cloud (AWS, Databricks ou similaires).
• Expérience avérée dans le déploiement à grande échelle de systèmes ML de production, et pas seulement de prototypes.
• Solide expérience en LLM, modélisation de séries chronologiques et détection d'anomalies pour les données du monde réel.
• Capacité avérée à diriger les décisions architecturales, à encadrer les développeurs(ses) et à collaborer avec les équipes chargées des produits, des données et des plateformes.
• Connaissance des outils MLOps (Docker, Kubernetes, Weights & Biases, MLflow, SageMaker).
• Diplôme de deuxième cycle (master/doctorat) en informatique, apprentissage automatique ou dans un domaine connexe préféré.

Une attention particulière est accordée aux candidats présentant les caractéristiques suivantes:

• Expérience avec l'OCR pour l'extraction de données structurées à partir de documents.
• Expérience dans la modélisation de séries chronologiques pour la maintenance prédictive et la détection d'anomalies.
• Connaissance des systèmes IoT industriels (capteurs, télémétrie, edge computing).
• Expérience dans l'application de l'apprentissage par renforcement ou des architectures agentuelles pour les systèmes de prise de décision et de contrôle.
• Contributions à des frameworks ML open source ou à la recherche dans les domaines de la fiabilité, de l'explicabilité ou des jumeaux numériques.

Quels sont les avantages pour vous?:

• Un salaire compétitif et des opportunités d'équité significatives.
• Couverture des soins de santé, des soins dentaires et de la vue.
• Programme d'inscription 401(k) / RRSP.
• Prenez les congés dont vous avez besoin.
• Une culture du travail :
• Vous travaillerez avec des personnes intelligentes, humbles et optimistes à travers le monde.
• Un environnement méritocratique où les idées et les résultats sont publiquement célébrés.

Qui sommes-nous:

MaintainX s'engage à créer un environnement diversifié. Tous les candidats qualifiés seront pris en considération pour un emploi sans considération de race, de couleur, de religion, de sexe, d'identité ou d'expression de genre, d'orientation sexuelle, d'origine nationale, de génétique, d'invalidité, d'âge ou de statut d'ancien combattant.

About the Data Science Organization 

Northbeam’s Data Science organization serves as the intelligence layer of the company, owning the end-to-end science behind marketing measurement and optimization. This includes developing and advancing our core methodologies—Media Mix Modeling (MMM), Incrementality testing, causal multi-touch attribution (MTA), calibration and validation frameworks, and large-scale experimentation systems. The team is also responsible for AI-driven insights, recommendations, and the creation of reusable, scalable, and rigorously validated scientific systems that power Northbeam’s product and customer value.

About the Role

We are seeking a Staff Data Scientist to advance the statistical and experimentation foundations of Northbeam’s marketing intelligence products, including MMM, Incrementality, Insights, and Recommendation engines.  This is a full-stack data scientist role, operating across the entire lifecycle—from researching and developing advanced statistical and causal inference approaches to implementing, deploying, and maintaining production systems.

You will work at the intersection of R&D and product, owning modeling end-to-end: from data exploration and experimental design to model validation, production integration, and live system iteration. You will bring a deep understanding of statistical modeling techniques and, critically, the assumptions underlying them. This role requires strong judgment in selecting, stress-testing, and adapting models to real-world marketing data where ideal conditions rarely exist.

This is a high-agency, hands-on role, requiring comfort shifting between deep technical work, cross-functional collaboration, and customer-facing problem solving as business needs evolve.

Your Impact

• Develop and evolve statistical and causal inference methodologies that strengthen the rigor and reliability of Northbeam’s marketing measurement products.
• Enhance the accuracy, robustness, and scalability of existing MMM pipelines.
• Write production-quality Python and SQL, collaborating closely with Engineering to integrate statistical workflows into scalable systems.
• Rigorously assess model assumptions, identify potential sources of bias, and implement mitigation strategies.
• Debug data and modeling issues in production and improve the reliability of customer-facing results.
• Translate complex statistical reasoning into clear, decision-ready insights for internal stakeholders and customers.

What You Bring

• Bachelor’s degree in Mathematics, Computer Science, or a highly quantitative STEM field (Master’s preferred).
• 6+ years of applied experience in data science, machine learning, or statistical modeling roles.
• Deep applied experience in statistics and causal inference, including hands-on ownership of experiment design (A/B testing, geo-based experiments, or quasi-experimental methods), power analysis, and interpretation of lift.
• Strong understanding of regression, time series modeling, Bayesian methods, and model evaluation in real-world business settings.
• Experience translating statistical research or experimentation frameworks into production-ready systems.
• Proficiency in Python and SQL, with experience working on modern data platforms and statistical modeling libraries.
• Experience working with production code and comfort making changes to live models and pipelines.
• Interest in (or prior experience with) marketing measurement, including MMM and incrementality, with a strong desire to deepen domain expertise.
• Thrives in a small, fast-paced environment, with the ability to drive projects end-to-end.
• Strong communication skills, with comfort explaining technical concepts to non-technical audiences and supporting customer-facing investigations.
• A growth mindset and genuine curiosity about improving measurement quality and decision-making.

Bonus Skills & Experience

• Experience in marketing attribution, MMM, incrementality, or related marketing measurement challenges.
• Experience with optimization techniques (e.g., linear programming, mixed-integer programming) applied in production systems.
• Familiarity with MLOps practices and data pipeline orchestration tools.
• Startup Experiences.
• PhD in a quantitative field. 

Why Northbeam

Unlike most Series A+ companies, we have a proven business model, strong revenue, and a growing waitlist of customers eager for the products we’re building. We are in a high growth phase and we are nearly profitable.

We sit at the center of the performance-marketing ecosystem with deep partnerships across major ad platforms (Meta, Snap, TikTok, AppLovin, and more). Our unique combination of high-quality partner integrations, rich 1st-party data, and a robust identity graph gives us an advantage that is extremely difficult for competitors to replicate.

Northbeam is where top-tier data talent can directly shape the industry’s most important measurement challenges at scale.

#LI-Remote

The Mission

We are seeking an Engineering Manager for our Cloud Data Engineering Practice. The right candidate is someone who is technically strong, can manage a team of Architects and Engineers, oversee data delivery engagements and is passionate about working with our customers, partners and employees to drive the business forward.

Your Assignment

• Manage a team of 5 - 8 cloud engineers and architects
• Interface with clients and internal teams to propose technical improvements using your cloud and engineering knowledge
• Take on hands-on technical responsibilities, including technical tasks in sprints 
• Lead technical discussions with customers
• Handle code reviews and pull request management
• Manage task assignments within sprints
• Perform technical leadership activities like roadmap and vision checks, best practices implementation, and risk identification
• In-project mentoring (understand people on project & creation of growth opportunities) and sharing feedback for team members on the project
• Technical accountability on the delivery
• Kickoff new client engagements and act as a point of technical escalation
• Develop and review proposals and contracts and present these to clients
• Perform technical interviews for Architect and Engineer candidates
• Perform weekly 1:1s with your direct reports and guide their career development
•  

Your Qualifications

• Strong experience in AWS data landscape
• Expertise in at least two major areas of Cloud Data Engineering:
  • Relational database design, optimization and migration
  • Big data processing using Spark, Hadoop, EMR etc
  • Machine Learning and MLOps
  • Advanced analytics using time series forecasting, descriptive and inferential statistics
  • BI dashboards and visualizations
  • Data Governance and MDM
• Experience with most of these:
  • Infrastructure as Code tools
  • CI/CD pipelines
  • Application modernization and migration with a strong focus on databases
• Excellent written and verbal communication skills

Benefits

• 100% remote work
• Equitable Life - Hybrid Plan
• 100% Premium Coverage for the employee and dependents
• Competitive phantom equity
• Long-Term Disability
• 4% Pension match (employer contribution)
• Unlimited Vacations
• Sick Leave 
• Paid Holidays 
• Parental Leave
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Base Salary Range: The expected base salary range for this position is CAD $152,000 - $193,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

Caylent is a place where everyone belongs.  We celebrate diversity and are committed to creating an inclusive environment for all employees. Our approach helps us to build a winning team that represents a variety of backgrounds, perspectives, and abilities. So, regardless of how your diversity expresses itself, you can find a home here at Caylent.   

We are proud to be an equal opportunity employer. We prohibit discrimination and harassment of any kind based on race, color, religion, national origin, sex (including pregnancy), sexual orientation, gender identity, gender expression, age, veteran status, genetic information, disability, or other applicable legally protected characteristics. If you would like to request an accommodation due to a disability, please contact us at hr@caylent.com. 

Viral Nation is seeking an AI Integration Engineer, AI/ML to serve as the primary technical engine translating high-level architectural visions into production-ready reality. Reporting directly to the Principal Architect, AI/ML and VP of Engineering, you will be responsible for the hands-on development, integration, and deployment of AI/ML models and agentic workflows within our GCP ecosystem.

What You'll Do Here:

• You will transform the Principal Architect’s reference architectures into scalable, deployable code using Python, GKE, and Cloud Run.
• Your primary focus involves building out agentic ecosystems using Google ADK (Agent Development Kit) and Model Context Protocol (MCP), specifically focusing on the Agent-to-Agent (A2A) orchestration patterns defined by the Architect.
• You will apply advanced prompt engineering and context engineering techniques to optimize LLM performance, ensuring agents maintain state and accuracy over long interactions.
• You will develop and tune high-fidelity RAG pipelines using the Google RAG Engine and Agent Engine to ensure agents have the precise context required for influencer marketing workflows.
• The role requires applying machine learning techniques to our massive datasets to implement automated anomaly detection, forecasting, and trend analysis.
• You will perform advanced data science and analysis by generating and querying high-dimensional video and text embeddings to extract insights from social media content.
• You will integrate Gemini and Model Garden LLMs into production applications while managing the technical nuances of token limits and context window optimization.
• Partnering with the Architect, you will implement MLOps practices that track agent performance, cost-efficiency, and ethical AI safeguards within the GCP IAM framework.

What You'll Need To Have:

• Advanced proficiency in Python is required for AI/ML backend development, data analysis, and API construction.
• You must possess a deep understanding of prompt engineering strategies (Chain-of-Thought, ReAct) and context engineering to maximize model reasoning capabilities.
• The position demands deep hands-on experience with Google ADK, MCP, Vertex AI Pipelines, and the Google RAG Engine.
• You should have practical experience applying classical ML algorithms for regression, forecasting, and anomaly detection on large-scale datasets.
• The role requires a strong understanding of vector databases and the manipulation of video/text embeddings for semantic search and classification.
• Deep experience with utilizing GitHub Actions to support the SDLC workflows and CI/CD standards established by the Principal Architect.

Nice To Haves

• Experience utilizing Snowflake Cortex Analyst, Cortex Search, and Snowflake Intelligence ecosystem.
• Proficiency in Node.js for full-stack integration layer and tool development is highly regarded.
• Prior experience in the digital marketing or influencer marketing space is a significant advantage.
• Experience with containerization and orchestration using Docker and GKE will help scale our autonomous systems.

Viral Nation is seeking an AI Integration Engineer, AI/ML to serve as the primary technical engine translating high-level architectural visions into production-ready reality. Reporting directly to the Principal Architect, AI/ML and VP of Engineering, you will be responsible for the hands-on development, integration, and deployment of AI/ML models and agentic workflows within our GCP ecosystem.

What You'll Do Here:

• You will transform the Principal Architect’s reference architectures into scalable, deployable code using Python, GKE, and Cloud Run.
• Your primary focus involves building out agentic ecosystems using Google ADK (Agent Development Kit) and Model Context Protocol (MCP), specifically focusing on the Agent-to-Agent (A2A) orchestration patterns defined by the Architect.
• You will apply advanced prompt engineering and context engineering techniques to optimize LLM performance, ensuring agents maintain state and accuracy over long interactions.
• You will develop and tune high-fidelity RAG pipelines using the Google RAG Engine and Agent Engine to ensure agents have the precise context required for influencer marketing workflows.
• The role requires applying machine learning techniques to our massive datasets to implement automated anomaly detection, forecasting, and trend analysis.
• You will perform advanced data science and analysis by generating and querying high-dimensional video and text embeddings to extract insights from social media content.
• You will integrate Gemini and Model Garden LLMs into production applications while managing the technical nuances of token limits and context window optimization.
• Partnering with the Architect, you will implement MLOps practices that track agent performance, cost-efficiency, and ethical AI safeguards within the GCP IAM framework.

What You'll Need To Have:

• Advanced proficiency in Python is required for AI/ML backend development, data analysis, and API construction.
• You must possess a deep understanding of prompt engineering strategies (Chain-of-Thought, ReAct) and context engineering to maximize model reasoning capabilities.
• The position demands deep hands-on experience with Google ADK, MCP, Vertex AI Pipelines, and the Google RAG Engine.
• You should have practical experience applying classical ML algorithms for regression, forecasting, and anomaly detection on large-scale datasets.
• The role requires a strong understanding of vector databases and the manipulation of video/text embeddings for semantic search and classification.
• Deep experience with utilizing GitHub Actions to support the SDLC workflows and CI/CD standards established by the Principal Architect.

Nice To Haves

• Experience utilizing Snowflake Cortex Analyst, Cortex Search, and Snowflake Intelligence ecosystem.
• Proficiency in Node.js for full-stack integration layer and tool development is highly regarded.
• Prior experience in the digital marketing or influencer marketing space is a significant advantage.
• Experience with containerization and orchestration using Docker and GKE will help scale our autonomous systems.

The Role

The Data Practice Director is a senior leadership role within Caylent's Cloud Data Engineering (CDE) practice, reporting directly to the Data Practice Leader. This person is responsible for operationalizing the practice strategy, leading a team of data professionals, and owning delivery excellence across a portfolio of client engagements. They are the connective tissue between strategic direction and day-to-day execution, ensuring the practice delivers consistent, high-quality outcomes while scaling to meet growth targets.

Your Assignment

Practice Operations and Delivery

• Own end-to-end delivery oversight for a portfolio of data engineering and analytics engagements, ensuring on-time, on-budget, and high-quality outcomes.
• Drive operational rigor across the practice including utilization management, staffing coordination, margin tracking, and engagement health reviews.
• Develop and enforce delivery standards, reusable frameworks, and best practices that enable consistent, scalable execution across the team.
• Serve as an escalation point for active engagements, helping resolve technical blockers, scope issues, and client concerns in partnership with delivery leads.
• Partner with the Practice Leader to translate the strategic roadmap into executable quarterly priorities and team-level OKRs.

Team Leadership and Development

• Directly lead and develop a team of data engineers, architects, and analytics professionals across the practice.
• Set clear performance expectations, conduct regular reviews, and provide ongoing coaching to build a high-performing, engaged team.
• Partner with recruiting and workforce planning to identify talent gaps, support hiring decisions, and onboard new team members effectively.
• Foster a culture of ownership, continuous learning, and technical excellence across a globally distributed team.
• Identify and develop emerging leaders within the practice, creating growth pathways aligned to practice needs.

Client Engagement

• Build trusted advisor relationships with key client stakeholders, acting as a senior point of contact for delivery and strategic guidance.
• Partner with the sales and GTM teams to support business development activities including scoping, proposal development, and technical solutioning for new and existing accounts.
• Identify and pursue expansion opportunities within active client engagements, surfacing new use cases and service offerings that align with client needs.
• Represent Caylent with credibility and professionalism in client-facing conversations at the director and VP level.

Practice Growth and Enablement

• Collaborate with the Practice Leader on go-to-market positioning, service offering development, and internal capability building.
• Contribute to thought leadership content including whitepapers, webinars, and conference presentations that elevate the practice's external profile.
• Stay current on trends in the modern data ecosystem and work with the team to incorporate relevant innovations into our delivery approach.
• Support the development of practice IP including accelerators, reference architectures, and reusable solution components.

Your Qualifications

Experience

• 12+ years of experience in professional services or consulting, with a strong focus on data engineering, analytics, or data platform delivery.
• Demonstrated success managing and growing a team of 20 or more data professionals in a services or consulting environment.
• Proven track record of delivering complex data projects on AWS, including data lake, lakehouse, streaming, and analytics workloads.
• Experience managing a portfolio of concurrent client engagements, balancing delivery quality with financial performance.
• Hands-on background in data architecture or engineering, with the ability to engage credibly with technical teams and client stakeholders alike.

Leadership

• Strong people management skills with demonstrated ability to develop talent, drive performance, and build team culture across geographies.
• Ability to operate effectively at multiple levels, from strategic planning conversations with the Practice Leader to hands-on engagement support with delivery teams.
• Comfortable navigating ambiguity and complexity in a fast-paced, high-growth consulting environment.
• Experience influencing senior client stakeholders (director, VP and C-level) in delivery and advisory contexts.

Technical Acumen

• Deep familiarity with the AWS data ecosystem including services such as Redshift, Glue, EMR, Kinesis, Lake Formation, and Athena.
• Working knowledge of adjacent platforms including Databricks and Snowflake, and their integration with AWS-native architectures.
• Broad understanding of data engineering fundamentals: ingestion patterns, transformation frameworks (e.g., Spark, dbt), data modeling, governance, and quality management.
• Familiarity with MLOps and data science workflows sufficient to support and position those capabilities in client conversations.

Education

• Bachelor's degree in Computer Science, Data Science, Information Systems, or a related field.
• Master's degree or MBA is a plus.

Certifications

• AWS Certified Data Analytics, AWS Certified Solutions Architect, or equivalent certifications are a plus.

Preferred Qualifications

• Execution-Oriented: Skilled at translating strategy into structured plans and holding teams accountable to outcomes.
• Client-First Mindset: Genuinely invested in client success and capable of building durable, trust-based relationships.
• Collaborative Partner: Works effectively across sales, delivery, and practice leadership functions without siloed thinking.
• Clear Communicator: Able to convey complex technical and business concepts to diverse audiences with clarity and confidence.
• Growth Driver: Passionate about building teams, capabilities, and client relationships that compound over time.

Benefits

• 100% remote work
• Medical Insurance for you and eligible dependents
• Generous holidays and flexible PTO
• Competitive phantom equity
• Paid for exams and certifications
• Peer bonus awards
• State of the art laptop and tools
• Equipment & Office Stipend
• Individual professional development plan
• Annual stipend for Learning and Development
• Work with an amazing worldwide team and in an incredible corporate culture

Base Salary Range: The expected base salary range for this position is CAD $207,000 - $272,000 per year, commensurate with experience and qualifications.

Additional Compensation Components: In addition to the base salary, the compensation package may include bonuses, commissions, equity, and other incentives. The specific components will vary depending on the role and individual and/or company performance.

The Opportunity

This is a senior technical client leadership role that blends deep hands-on ML expertise with strategic advisory and consulting skills. You will be the most experienced ML voice across a diverse and expanding book of customer engagements — from early-stage companies bringing ambitious ML ideas to market, to established enterprises modernizing how they build and operate AI systems on AWS.

You will shape strategy, influence architecture, and leave every team you touch better than you found it. You bring the scientific depth to design and evaluate models rigorously, the engineering depth to architect production ML systems at scale, and the consulting instincts to translate both into business value for customers.

If you have led the hard conversations, shaped the architecture decisions that mattered, and built the things others benchmark against — and you are looking to do that across a growing portfolio of varied and interesting customers — this is the role for you.

What You'll Do

• Lead end-to-end ML assessments across infrastructure, data pipelines, model lifecycle, and organizational readiness — producing recommendations that drive executive decision-making and earn Caylent the next engagement.
• Partner with sales and solutions teams through the proposal and scoping phase, contributing the technical depth needed to shape well-grounded statements of work.
• Serve as the senior technical authority on client engagements — possibly across multiple projects simultaneously — providing architectural guidance, ensuring technical quality from your project team members, and getting hands-on when the engagement demands it, without owning day-to-day implementation responsibilities.
• Own or orchestrate high-quality POCs that give customers confidence before committing to a larger initiative.
• Advise customers on ML operations standards and architecture — covering MLOps pipeline design, model lifecycle management, LLMOps patterns, and production monitoring frameworks — translating operational complexity into decisions and guardrails their teams can own and sustain.
• Shape how Caylent wins its most technically complex opportunities — contributing the architectural thinking and credibility that turns prospects into customers.
• Strengthen the ML practice from the inside — through peer guidance, technical interviews, and contributions to accelerators, reference architectures, and thought leadership content.

What You Bring

The non-negotiables

• 10+ years in machine learning or AI, with a proven track record of leading client-facing engagements in a consulting or advisory capacity.
• Deep, current knowledge of the AWS ML and GenAI ecosystem, with the ability to make and defend architectural decisions across the full ML lifecycle — from data and feature engineering through training, deployment, and monitoring.
• Deep expertise in at least two or three ML domains — whether traditional ML, computer vision, NLP, time series, or others — combined with the judgment to assess, architect, and advise across the broader ML landscape.
• Proven ability to architect and govern production ML systems end-to-end, translating MLOps, LLMOps, and broader AI operations complexity into standards and decisions that engineering teams can execute and executives can act on.
• Deep expertise across foundation model adaptation — fine-tuning (LoRA, QLoRA, PEFT), alignment (RLHF, DPO), inference optimization (quantization, vLLM), and distributed training (DeepSpeed, FSDP) — combined with RAG and agentic system design, including multi-agent architectures, event-driven workflows, MCP integration, and human-in-the-loop patterns on AWS. Technical authority to prescribe the right approach and set architectural standards that teams can execute against.
• Proven ability to operate independently in complex customer environments — navigating ambiguity, aligning stakeholders, and translating ML tradeoffs into business risk and value for both technical and executive audiences.

Strong differentiators

• AWS Certified Machine Learning – Specialty and/or AWS Certified Solutions Architect – Professional.
• Experience shaping practice-level standards, reference architectures, and reusable ML accelerators across multiple engagements.
• Exposure to varied industries and problem types in a consulting or client-facing context.
• Deep fluency in responsible AI practices — model evaluation, bias detection, fairness frameworks, and AI governance — applied in enterprise deployments.
• Hands-on experience designing and deploying SRE agents and AI-driven operations workflows in production — spanning automated incident detection, triage, and remediation — with the ability to integrate across observability platforms and translate AI operations outcomes into measurable business value.

Technical Stack

Our practice spans a broad range of ML domains. Candidates are expected to prescribe — not just recognize — with the judgment to maximize what AWS makes possible and the experience to know how open-source tooling strengthens it.

ML Domains: Classical ML, Computer Vision, NLP, Generative AI & LLMs, AI Agents & Autonomous Systems, Intelligent Document Processing, Video Understanding, Speech & Audio, Time Series & Forecasting, Recommender Systems, Graph ML, Reinforcement Learning, Multimodal AI

AWS ML Platform: SageMaker, SageMaker Pipelines, SageMaker Feature Store, SageMaker Model Registry, SageMaker Clarify, Bedrock (Agents, Knowledge Bases, Guardrails, AgentCore, Model Evaluation)

Multi-provider LLM: Bedrock, Anthropic API, OpenAI API, Google Gemini API, Azure OpenAI — with the judgment to reason across provider tradeoffs in enterprise contexts

AWS AI Services: Rekognition, Comprehend, Transcribe, Textract, Translate, Personalize, Neptune, Kinesis Video Streams, Polly

Data Platform: Apache Spark / PySpark, Apache Kafka, Amazon Kinesis, Apache Iceberg, Delta Lake, Apache Hudi, AWS Glue

Vector Databases: Pinecone, pgvector, Amazon OpenSearch (vector), Weaviate

Frameworks: PyTorch, TensorFlow, JAX, Scikit-learn, XGBoost, HuggingFace (Transformers, PEFT, TRL), LangChain, LlamaIndex, DSPy, Ollama

MLOps & Governance: MLflow, W&B, Airflow / MWAA (data orchestration), Dagster (asset-based pipelines), Kubeflow Pipelines, CI/CD, IaC (CloudFormation, CDK, Terraform), Docker, Kubernetes, ML Governance (lineage, data contracts, audit), Responsible AI / Bias & Fairness

LLM Evaluation & Safety: RAGAS, LLM-as-judge patterns, DeepEval, NeMo Guardrails, Constitutional AI patterns, structured output validation

Inference & Optimization: Triton, vLLM, SGLang, Trainium, Inferentia, Quantization (GPTQ, AWQ, bitsandbytes), SageMaker Neo

The role

Are you passionate about food? Do you consider yourself an expert and enthusiast in developing and deploying large-scale recommender systems? Then this position might be the perfect fit for you!

You will join a high-impact team of data scientists, focusing exclusively on menu personalization. As a Senior Data Scientist, you will play a pivotal role in designing, implementing, and improving our personalized recommendation algorithms for culinary products across HelloFresh’s global markets. In this role, you can expect to have a large and tangible impact on customer experience and business growth by ensuring customers always see the most relevant and appealing menu options. You will work closely with other personalization Data Scientists, as well as Data, Backend, and Machine Learning Engineers, together delivering statistical solutions and ML models to production.

To succeed in this role you should be curious, able to deal with uncertainty, a fast learner, and someone who relentlessly prioritizes problem statements and tailors the solution accordingly. You should also be comfortable suggesting multiple solutions based on your experience, and prioritizing tasks based on effort and potential impact. As a senior member of the team, you will be expected to work independently when necessary, as well as support other team members occasionally. 

What you’ll do

• Join and become an integral part of a high-impact team covering menu personalization.
• Contribute to designing and implementing the next generation of our recommender models, from experimentation and data collection to operationalization and closely aligning them with non-technical stakeholders.
• Shape and transform the future of customer experience at HelloFresh by proposing new personalization approaches and evolving the statistical and ML models in pace with future company strategies.
• Design and execute A/B tests to measure the impact of new recommendation strategies on key metrics.
• Work with state-of-the-art technologies like AWS (EMR, Glue, S3, etc), Kafka, PySpark, Airflow, Databricks, MLFlow, Claude (AI), as well as our in-house MLOPs tools.
• Collaborate closely within other functions (data engineering, backend engineering, ML engineering, product) to translate business objectives into concrete, data-driven personalization strategies.
• Analyze the performance of our models to understand customer behavior, and come up with improvements.
• Contribute to a collaborative and knowledge-sharing environment.

What you’ll bring

• Proven track record of scientific work in your Bachelor's, Master's, or PhD in computer science, statistics, physics, economics, mathematics, data science or similar.
• Long-term (3+ yrs) work experience as a (senior) data scientist focused on developing and deploying recommender systems or personalized ML models in a production environment.
• In-depth knowledge of various recommendation algorithms, evaluation metrics, and the practical challenges of building and maintaining a modern recommender system.
• Fluency and long-term experience in Python, including high familiarity with its scientific stack such as Numpy, Pandas, Scikit-learn, Matplotlib. (Experience in Databricks and PySpark is a plus).
• Ability to retrieve (using SQL), manipulate, and analyse large, heterogeneous datasets.
• Experience with software development practices and tools (Git, CI/CD, Docker, AWS).
• You love to learn, are a critical thinker and creative problem solver who strives for excellence.
• You are a team player who loves to collaborate and work with stakeholders from different backgrounds in an international environment.
• Exceptional communication and collaboration capabilities.
• Experience working with and leveraging Generative AI tools (e.g., Claude, Copilot) to support model development, experimentation, code generation, and documentation.

Interacting with product managers, UX designers, data and backend engineers, as well as business stakeholders, is very much part of our day-to-day, so communication skills are vital. We are looking for strong problem-solvers who can apply their statistical modeling and machine learning skills to a wide range of business problems in the personalization space while also acting as an ambassador to coach team members and stakeholders.

Above all, we are looking for people who will make HelloFresh better. We believe there are many different ways of developing skills, and we love diverse experiences! So even if you don’t “tick all the boxes” but think you’d thrive in this role, we would really like to learn more about you.

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

#DATA

Figma seeks an AI-Native Performance TPM to own performance prevention, diagnostics, and safe rollout for both our flagship products and next-gen AI features. This platform-level role spans desktop, browser and mobile; requires deep experience with performance testing (load, stress, endurance, interference), observability, and incident response. You’ll partner across Product, Platform, Performance Program and Product Support. Join us to keep Figma snappy quick!

This is a full time role that can be held from one of our US hubs or remotely in the United States. 

What you'll do at Figma:

• This is a specialist Platform TPM owning horizontal, high-visibility performance programs that span:
• Flagship product performance (load times, FPS, memory) and AI features (model inference latency, throughput, cost, and reliability)
• Desktop, browser, native mobile (React Native / WebView), and WASM contexts
• Cross-org programs: observability/telemetry, regression prevention (performance CI), xfn performance forum, SEV mitigation, safe rollout of AI capabilities, and CE Planning (customer engineering / enterprise readiness)

We’d love to hear from you if you have:

• 5+ years in performance engineering, performance TPM, platform TPM, or SRE with hands-on experience shipping performance programs for SaaS products
• Demonstrated experience with load, stress, performance or scalability testing and new-build comparisons
• Deep familiarity with web performance (FCP, LCP), rendering/FPS, WASM memory, mobile profiling (Xcode Instruments, Android Profiler)
• CI/CD and test automation experience: integrating performance tests into pipelines 
• Distributed systems, cloud infra (AWS), autoscaling, and capacity planning
• Hands-on prior work with LLMs, prompt engineering, or agent platforms

While it’s not required, it’s an added plus if you also have:

• Experience with MLops or LLMs: inference latency tradeoffs, batching, caching, etc
• Observability stack: Datadog / Sentry / RUM
• Background as a performance engineer (not just TPM) with code or test harness contributions.
• Experience with large enterprise Planning / customer load tests.
• Familiarity with real-time collaborative systems and GPU/WASM performance constraints.

Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network. 

This role is part of the AI Platform team, which owns the AI services that power Affinity's industry-leading relationship intelligence platform. We extract and retrieve information from billions of structured and unstructured data points to deliver actionable insights to customers.

As a Senior AI Engineer, you will collaborate with machine learning engineers, data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will design and build LLM-powered AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry. 

In this role you will:

• Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques. 
• Build LLM powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers. 
• Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data. 
• Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) to build robust, high-scale systems that underlie all of our data processing and ML Operations.

Qualifications

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Required:

• 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production. 
• Hands on experience with LLM applications in production including prompt engineering and utilizing frameworks for online and offline evaluation
• Experience with LLM assisted search, such as query understanding and augmentation, text2sql, and entity extraction   
• Experience with vector or graph databases
• Experience with document chunking, embedding models, and context window optimization
• Familiarity with metadata-based retrieval and re-ranking strategies
• Hands on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)   
• Familiarity with data security, versioning, and MLOps principles

Nice to Have:

• Experience with enterprise AI applications with strict compliance, audit, or legal requirements
• Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvements. 
• Experience with multi-modal search
• Experience with graph based recommendation systems, such as graph NN. 
• Experience with developing AI applications powered by agent-based systems
• Experience with packaging, CI/CD and pipeline automation. 

Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference. 

How we work:

Our culture is a key part of how we operate, as well as our hiring process:

• We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
• We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with. 
• We make data-driven decisions and make the best decision for the moment based on the information available.

If you’d want to learn more about our values click here.

What you'll enjoy at Affinity:

• We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
• Health Benefits: We cover both you and your dependents' extended health benefit premiums and offer flexible personal & sick days to support your well-being.
• Retirement Planning: We offer an RRSP plan to help you plan for your future.
• Learning & Development: We provide an annual education budget and a comprehensive L&D program.
• Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
• Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.

A reasonable estimate of the current range is $160,000 to $220,000 CAD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant. 

At Affinity, we may use artificial intelligence (AI) tools as part of our recruitment process to help screen and evaluate candidate applications. While AI assists our hiring team in managing applications efficiently, it never replaces decisions made by real people. We are committed to fair and transparent hiring practices, and our AI tools are regularly monitored to ensure they support—not replace—human judgment. 

Additional Information:

• This job posting represents an active vacancy that we are currently seeking to fill.

About the Role 

We are seeking a visionary and highly motivated AI Factory Program Manager to drive the development and delivery of our AI Factory platform. This unique hybrid role requires a strong blend of program management, Scrum Master expertise, and product ownership to ensure the AI Factory operates efficiently, delivers high-quality AI solutions, and aligns with strategic business goals. This role will be instrumental in bridging the technical AI teams with business stakeholders.

Key Responsibilities

Project Management & Scrum Master (50%)

• Agile Leadership: Serve as the Scrum Master for multiple AI development teams, facilitating all Scrum ceremonies (sprint planning, daily stand-ups, reviews, and retrospectives).
• Process Optimization: Implement and continuously improve agile methodologies and processes tailored for AI/ML development, including managing data dependencies, model training pipelines, and MLOps workflows.
• Risk & Impediment Management: Proactively identify, track, and remove impediments, risks, and dependencies that could block team progress, particularly those related to data, infrastructure, and cross-functional teams.
• Reporting & Communication: Monitor and report on key program metrics, team velocity, and project status to stakeholders, ensuring transparency and alignment across the AI Factory.

Product Owner (50%)

• Vision & Strategy: Define and articulate the product vision and strategy for specific components or services within the AI Factory, ensuring alignment with the overall business and AI strategy.
• Backlog Management: Own, prioritize, and maintain the product backlog for the AI team, clearly defining user stories, acceptance criteria, and epics for new AI features, models, and platform capabilities.
• Stakeholder Alignment: Serve as the primary liaison between the AI development team and key internal stakeholders (e.g., business unit leads, data science, engineering) to gather requirements and communicate progress.
• Value Maximization: Continuously assess and track the business value delivered by the AI models and platforms, guiding the team to prioritize work that maximizes ROI and customer impact.

Required Experience:

• Education: Bachelor's degree in Computer Science, Engineering, Business, or a related field or equivalent experience.
• Experience: 8+ years of progressive experience in technical program management, product management, or a similar role, with at least 2 years focused on AI, Machine Learning, or Data Science initiatives.
• Certifications: Certified Scrum Master (CSM) or equivalent certification or experience.
• Agile Leadership: Proven ability to lead complex, cross-functional projects in an Agile environment.
• Communication: Exceptional communication, negotiation, and conflict-resolution skills.

Job Location – Remote (USA & Canada)

The expected base salary for this position is: CAD 190000/ USD 195,000 excluding annual bonus (when applicable). Salary is based on a number of factors including market conditions, location and may vary depending on job-related skills and experience.

The Connectors team is the bridge between ClickHouse and the broader data ecosystem. We build and maintain the integrations that make ClickHouse accessible to millions of developers, data practitioners, and AI agents worldwide from high-level data visualization plugins (Tableau, PowerBI, Superset, Metabase) to connectors for data frameworks (Apache Spark, Flink, Kafka Connect, Fivetran), orchestration platforms, and AI tooling.

Our work directly shapes how companies process massive datasets: real-time analytics platforms ingesting millions of events per second, observability systems monitoring global infrastructure, and increasingly, the AI-powered data applications redefining how teams work with data. We collaborate closely with the open-source community, internal teams, and enterprise users to ensure ClickHouse integrations set the standard for performance, reliability, and developer experience.

About the role

As a Senior Software Engineer specializing in Python and the Data Ecosystem, you'll be a core contributor owning and evolving critical parts of ClickHouse's data engineering ecosystem. This role sits at the intersection of high-performance database engineering and developer experience. You'll craft tools that enable Data Engineers and Data Scientists to harness ClickHouse's speed and scale in the frameworks they already use.

We're looking for someone who has lived the Data Engineer or Data Scientist experience firsthand. The data practitioner's world is shifting rapidly: databases are no longer just query targets, but they're becoming active participants in AI-powered workflows, serving as vector stores for RAG pipelines, backends for LLM-powered agents, and real-time feature stores for ML inference. You understand these workflows not from the outside, but because you've operated within them. You don't just build integrations, you bring product-level insight into what we should build and why.

You'll own the full lifecycle of key Python integrations, driving architecture, performance, and feature direction across:

• Orchestration Platforms: Apache Airflow, Dagster, Prefect
• Transformation Tools: dbt, SQLMesh
• AI & LLM Ecosystem: LangChain, LlamaIndex, n8n, and broader AI tooling: embedding pipelines, retrieval-augmented generation with ClickHouse as a vector store, ML feature stores, and LLM-powered data applications

ClickHouse's columnar architecture and query performance make it exceptionally well-positioned in this new landscape. Your job is to make that potential real:  building the robust, production-ready connectors that make ClickHouse the natural choice when data practitioners design their next-generation AI and data systems.

What you'll do

• Own and evolve ClickHouse's Python connector and SDK ecosystem, raising the bar on performance, reliability, and API design
• Build and maintain integrations with orchestration platforms (Airflow, Dagster, Prefect) and transformation tools (dbt) to enterprise-grade quality standards
• Drive the AI/LLM integration strategy:  designing connectors and patterns that make ClickHouse a natural fit in RAG architectures, ML feature pipelines, and LLM-powered data applications
• Engage actively with the open-source community: triage issues, support contributors, advocate for users, and shape the roadmap based on real-world feedback
• Collaborate with Product, Cloud, and other engineering teams to align integration work with broader platform priorities
• Bring a practitioner's perspective to roadmap decisions, grounding prioritization in genuine Data Engineer and Data Scientist workflows

About you

• 7+ years of software development experience, ideally with hands-on time as a Data Engineer, Data Scientist, or ML Engineer
• Deep, proven experience designing, building, and maintaining production-grade Python connectors, SDKs, or integrations for at least one major platform (orchestration, BI, MLOps, or data transformation)
• Solid experience with the Python data ecosystem: Pandas, NumPy, Pydantic, and related libraries
• Prior contributions to, or deep practical experience with, popular data orchestration tools (Airflow, Dagster, or Prefect)
• Hands-on experience with AI/ML in data engineering contexts: embedding generation, vector search, feature pipelines, or LLM-powered tooling in production, not just experimentation
• Strong understanding of database fundamentals: SQL, data modeling, query optimization, and familiarity with OLAP/analytical databases
• Solid experience with concurrent Python: threading, multiprocessing, and async patterns
• Outstanding written and verbal communication skills; comfortable collaborating across engineering functions and with open-source communities

Bonus points for:

• Experience deploying AI/ML models in production, including inference APIs and vector databases
• Prior experience as a Data Engineer or Data Scientist in a product-facing or platform role
• Familiarity with ClickHouse or similar high-performance OLAP platforms
• Familiarity with the JVM ecosystem

The Role

We are seeking a Senior AI Engineer to join our AI & Data Group on the AI Orchestration team. This role is responsible for designing, building, operating and scaling the orchestration layer that powers League’s AI-driven healthcare experiences. 

Sitting at the intersection of AI systems design, ML productionization, and distributed software engineering, you will take the probabilistic capabilities of large language models and engineer them into reliable, measurable, and scalable product experiences.

This is a hands-on senior engineering role for a practitioner who moves beyond prototypes to own the hard problem of making AI work at scale. You will translate leading edge AI innovation into reliable, secure, and compliant systems. Your work will directly impact how AI is operationalized across League’s digital health ecosystem—ensuring systems are scalable, observable, performant, and safe in a regulated environment.

À propos de l’entreprise  

À Torc, nous avons toujours cru que la technologie des véhicules autonomes transformera la façon dont nous voyageons, transportons la marchandise et faisons des affaires.  

Leader de la conduite autonome depuis 2007, Torc a passé plus d’une décennie à commercialiser des solutions aux côtés de partenaires chevronnés. Nous faisons maintenant partie de la famille Daimler, ce qui nous permet de nous concentrer uniquement sur le développement de logiciels pour les camions automatisés. Nous transformerons la façon dont le monde transporte la marchandise.  

Joignez-vous à notre équipe : catapultez votre carrière au sein de l’entreprise ayant contribué à créer la technologie de conduite autonome (CA). Nous sommes la première entreprise de logiciels de CA ayant eu la vision de faire équipe directement avec un constructeur de camions.  

Rencontrez l’équipe :    

Torc va de l’avant avec sa stratégie AV 3.0. Les composants Simulation et Production de données sont majeurs pour le camionnage autonome. L’équipe élabore la simulation des capteurs en fonction des modèles de rendu neuronal et génératifs pour le simulateur guidé par les données de Torc. Les données de grande qualité provenant de mises en situation originales viennent combler l’écart des données du domaine, résolvant l’un des plus grands défis pour une conduite autonome sécuritaire.  L’équipe travaille sur des approches à la fine pointe pour le rendu neuronal et la production de données pour les données des capteurs des caméras, lidars et radars. Le tout contribue au flux de données de Torc pour l’entraînement et la validation à travers toute la pile AV.  

Ce que vous ferez :    

• Mettre en œuvre les dernières avancées en matière de recherche pour les modèles de rendu neuronal et génératifs
• Convertir les solutions à la fine pointe de la technologie dans le domaine de la conduite autonome pour les simulations des capteurs des caméras, lidars et radars
• Contribuer à la mise en œuvre d’un cadre de rendu neuronal qui permet la mise à l’échelle de la simulation de perception et de l’entraînement AV 3.0.
• Intégrer le cadre dans un environnement en nuage et automatiser le pipeline pour permettre la mise à l’échelle de la vérification et de la validation ciblées de nos camions autonomes
• Prendre la responsabilité des projets de développement dans l’équipe, de la recherche à la conception, en passant par la mise en œuvre, les tests et le déploiement
• Concevoir, mettre en œuvre, tester et déployer un logiciel livrable, prêt pour la phase de production, à partir de prototypes précoces avec des processus disciplinés en développement de logiciel.
• Travailler dans l’écosystème d’apprentissage automatique en nuage avec d’autres départements connexes existants au sein de l’entreprise.
• Évaluer de manière proactive les capacités actuelles pour identifier les domaines à améliorer, en proposant des solutions alignées sur la stratégie et les opérations fondamentales. 
• Démontrer des compétences en gestion de projet, servir de leader pour les membres de l’équipe moins expérimentés dans plusieurs facettes de l’exécution de projet, faire du coaching et du mentorat au besoin.

Ce dont vous aurez besoin pour réussir :    

• Maîtrise de Python et des cadres d’apprentissage profond comme PyTorch.
• Doctorat ou expérience de travail équivalente d’au moins 6 ans dans des domaines connexes (informatique, robotique, génie électrique) avec une expérience en logiciels d’expédition de production.
• Expertise éprouvée en rendu neuronal (champs de radiance neuronale et éclaboussures gaussiennes 3D) et modèles génératifs (modèles de diffusion, « flow matching »).
• Expérience en infographie, reconstruction 3D ou vision par ordinateur 3D.
• Considéré comme hautement qualifié(e) et compétent(e) dans sa discipline; réalise des travaux complexes et importants sous une supervision minimale et avec une grande latitude pour le jugement indépendant. 
• Expérience avec l’infrastructure de bureau virtuel (VDI) et les environnements de développement d’apprentissage automatique en nuage.
• Est censé piloter l’harmonisation entre les interfaces de l’équipe et le reste de l’organisation.
• Conçoit, maintient et est propriétaire des solutions techniques de l’équipe et favorise le consensus. 
• Mentore et guide les ingénieur·e·s du groupe.  

Points bonus! 

• Expérience de la conduite autonome ou de la perception robotique dans des environnements de production.
• Compétences en programmation CUDA pour un rendu efficace de scènes à grande échelle
• Publications pour des conférences de premier ordre en informatique/IA/infographie (CVPR/ECCV/ICCV, NeurIPS/ICLR/ICML, SIGGRAPH) ou dans des revues
• Expérience des outils MLOps et d’infrastructure (Ray)
• Familiarité avec l’étiquetage 3D, l’étalonnage et les pipelines de simulation de capteurs.
• Gestion de capteurs de conduite autonome - Plusieurs données avec horodatage, plusieurs données de capteurs des caméras, lidars et radars

La connaissance de l’anglais est exigée puisque la personne retenue devra collaborer de façon journalière avec des collègues anglophones aux États-Unis et travailler avec la documentation technique rédigée uniquement en anglais.

Les avantages de faire partie de l’équipe de Torc à temps plein  

Torc se soucie des membres de son équipe. Nous souhaitons leur offrir des avantages et mettre des ressources à leur disposition pour soutenir leur santé, leur équilibre vie professionnelle et vie privée ainsi que leur avenir. Notre culture est collaborative, énergique et centrée sur l’équipe. Torc offre ce qui suit :    

• Programme de rémunération concurrentiel qui comprend des options de primes et d’actions
• Primes médicales, dentaires et pour soins ophtalmologiques à 100 % pour les membres du personnel à temps plein.
• Régime Enregistré d’Épargne-Retraite (R.E.E.R) avec une contrepartie de 6 % de l’employeur
• Flexibilité de l’horaire et généreux congés payés (disponibles immédiatement après la date d’entrée en fonction).
• AD+D et assurance-vie

À Torc, nous nous engageons à cultiver un milieu de travail diversifié et inclusif. Nous célébrons l’unicité de chaque membre de l’équipe de Torc. Nous ne faisons pas de discrimination par rapport à l’origine ethnique, la religion, la couleur de peau, la nationalité, le genre (y compris la grossesse, les enfants ou autre condition médicale), l’orientation sexuelle, l’identité de genre, l’expression de genre, l’âge, le statut de vétéran ou les handicaps. 

Même si vous ne répondez pas à 100 % des qualifications énumérées pour ce poste, nous vous invitons à postuler. 

La rémunération que nous offrons reflète les coûts de la main-d’œuvre de plusieurs marchés géographiques. Le salaire dépend d’un certain nombre de facteurs et peut varier en fonction des connaissances, des compétences et de l’expérience en lien avec le poste. La rémunération globale offerte par Torc comprendra aussi la prime d’entreprise et l’option d’achat d’actions. Selon le poste offert, des paiements relatifs à l’entrée en fonction ou des frais de déménagement ainsi que toute autre forme de compensation peuvent être compris dans une rémunération globale, en plus d’un éventail complet d’avantages médicaux, financiers et autres.

Échelle salariale de base aux É.-U. :

160 800 $ à 212 300 $

Numéro du poste : R-102432

À propos de l’entreprise  

À Torc, nous avons toujours cru que la technologie des véhicules autonomes transformera la façon dont nous voyageons, transportons la marchandise et faisons des affaires.  

Leader de la conduite autonome depuis 2007, Torc a passé plus d’une décennie à commercialiser des solutions aux côtés de partenaires chevronnés. Nous faisons maintenant partie de la famille Daimler, ce qui nous permet de nous concentrer uniquement sur le développement de logiciels pour les camions automatisés. Nous transformerons la façon dont le monde transporte la marchandise.  

Joignez-vous à notre équipe : catapultez votre carrière au sein de l’entreprise ayant contribué à créer la technologie de conduite autonome (CA). Nous sommes la première entreprise de logiciels de CA ayant eu la vision de faire équipe directement avec un constructeur de camions. 

Rencontrez l’équipe 

L’objectif de l’équipe de pseudo-étiquetage est de créer des annotations de haute qualité sur les données de capteurs (images, nuages de points). Les annotations comprennent des boîtes englobantes 2D et 3D, des classes, des trajectoires, des lignes de voie, des segmentations, des profondeurs, etc. Les annotations sont ensuite utilisées par différents utilisateurs en aval; par exemple, les équipes de perception les utilisent pour entraîner divers modèles et les équipes de simulation les utilisent pour générer de nouvelles données. 

Ce que vous ferez 

• Conception, mise en œuvre, test et déploiement de modules de détection, suivi et fusion d’objets hors ligne pour créer automatiquement des annotations sur des Services d’infonuagique à partir de données de capteurs enregistrées (Caméras, Lidars, Radars)
• Compétences en gestion de projet démontrées, à titre de chef de projet guidant une équipe dont les membres possèdent peu d’expérience dans plusieurs volets de l’exécution du projet. 
• Restez au fait des derniers développements en matière d’IA et d’apprentissage automatique pour la conduite autonome.
• Développer indépendamment des modèles ou des algorithmes de perception hors ligne en utilisant des processus de développement logiciel disciplinés, en faisant des recommandations pour le développement de nouveau code ou la réutilisation de code existant, en mettant en œuvre le contrôle de version et en maintenant 
• Documentation des applications créées. 
• Définir et mettre en œuvre l’ingestion, la préparation, la curation et la gouvernance de grands ensembles de données multidimensionnels à l’appui des modèles et des flux de travail analytiques. 
• Évaluer de manière proactive les capacités actuelles pour identifier les domaines à améliorer, en proposant des solutions alignées sur la stratégie et les opérations fondamentales. 
• Mesurer et suivre la qualité de l’étiquetage automatique pour répondre aux exigences de la clientèle interne.
• Guider et produire des produits d’information, en soutenant la visualisation et l’accessibilité des données de manière centrée sur la clientèle. 
• Évaluer et faire des recommandations concernant les avancées techniques qui améliorent la productivité et la qualité, réduisent les délais d’exécution et renforcent la fiabilité opérationnelle. 
• Élaborer des directives et des normes pour les modèles d’analyse et d’apprentissage automatique, leur déploiement et les processus associés.  
• Fournit des conseils techniques ou une expertise en processus métier, un leadership technique, du coaching et du mentorat aux membres de l’équipe.  

Ce dont vous aurez besoin pour réussir 

• Considéré comme hautement qualifié(e) et compétent(e) dans sa discipline; réalise des travaux complexes et importants sous une supervision minimale et avec une grande latitude pour le jugement indépendant. 
• Portée d’influence : Est censé piloter l’harmonisation entre les interfaces de l’équipe et le reste de l’organisation. Conçoit, maintient et est propriétaire des solutions techniques de l’équipe et favorise le consensus. Effectue le mentorat et guide les ingénieurs du groupe.  
• Diplôme de licence en informatique, robotique, génie électrique ou dans un domaine technique connexe, plus des compétences et des aptitudes techniques démontrées généralement acquises par plus de 6 ans d’expérience OU;  
• Maîtrise en informatique, robotique, génie électrique ou domaine technique connexe, démontrant des compétences et des connaissances techniques généralement acquises par plus de 3 années d’expérience OU; 
• Doctorat en informatique, robotique, génie électrique ou domaine technique connexe, ainsi que des compétences et maîtrises techniques démontrées, généralement acquises après plus d’un an d’expérience. 
• Qualifications requises (une combinaison des compétences suivantes) :    
• Apprentissage actif et pseudo-étiquetage - Vision par ordinateur, apprentissage approfondi, entraînement de modèles
• Deux des éléments suivants : Détection d’objets 2D/3D, Suivi, Fusion de capteurs, Segmentation sémantique, SLAM, BEV
• Opérations et outillage d’apprentissage automatique à grande échelle (MLOps) – Cadres en apprentissage automatique, suivi d’expériences, registre de modèles, MLFLow, Poids et biais, métriques et évaluation/qualité en apprentissage automatique
• Cadre en apprentissage automatique distribué - PyTorch, Lightning, Ray
• Curation de données de modèle - Traitement de données Parquet (PyArrow, Daft, Pandas, etc.)
• Outils de développement et écosystème (à grande échelle) - Maîtrise du développement logiciel en Python. Aussi, environnements de développement VDI et infonuagique, systèmes d’intégration continue (GitHub Actions) et Docker