Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

Are you looking to thrive in a stimulating work environment?  

Join Levio, a leader in digital transformation, and take your career to the next level. You will work alongside high-caliber professionals on ambitious, large-scale technology projects, directly embedded in our clients’ environments. At Levio, we value expertise, curiosity, and continuous improvement — and we give you the space to grow.  

About the Role

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.

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

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. 

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:

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. 

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.

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

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

WHAT YOU'LL DO

Join the AI Platform team at Braze to build and scale BrazeAI Decisioning Studio - a reinforcement learning platform at the forefront of AI Decisioning. The platform runs continuous experimentation and personalizes customer engagement at the individual level, helping brands move from rule-based campaigns to autonomous, self-optimizing interactions. You'll work at the intersection of cloud-native infrastructure, data-intensive systems, and machine learning in production.

Main responsibilities:

• Build and maintain critical services and subsystems on our AI platform, balancing performance with cost-effective operations
• Implement cloud-native solutions that ensure reliability, scalability, and fault tolerance
• Troubleshoot production incidents end-to-end, going deep to identify root causes and implement durable fixes
• Contribute to observability practices using Sentry and Datadog to proactively detect issues and minimize downtime
• Collaborate with data scientists, ML engineers, and product teams to translate real-world use cases into platform capabilities
• Improve developer experience by streamlining workflows, enhancing tooling, and supporting MLOps best practices

Tech stack:

• Core Data & ML: Python, Ibis, FastAPI, Dataproc (Spark), SQL, BigQuery, MLflow, Streamlit
• Platform & Infrastructure: Google Cloud Platform, AWS, Kubernetes, Helm, Terraform
• Workflows & Orchestration: Airflow, RabbitMQ, Celery
• CI/CD: GitHub Actions, Jenkins
• Observability: Sentry, Datadog

Why this role:

• Production ML at scale: no toy datasets or notebook demos; you’re building infrastructure that powers real AI workloads
• Engineering rigor: unit and integration tests, modular design, CI/CD, pair programming, and code reviews are how we work, not aspirations
• Learn continuously: deep exposure to ML system architecture, end-to-end ML workflows, and reinforcement learning systems

WHO YOU ARE

• 2-4 years of experience in platform engineering, infrastructure, or a related backend role
• Solid understanding of platform architecture, particularly in ML or data-intensive environments
• Hands-on experience with Kubernetes and cloud infrastructure (GCP preferred)
• Ability to troubleshoot complex distributed systems under pressure
• Writes clean, modular code with a focus on testable APIs and maintainable design
• Experience working with AI coding assistants. Understands effective prompting strategies and can articulate when these tools add value versus when they're not appropriate
• Clear communicator who can work across technical and non-technical stakeholders
• Proactive problem solver who identifies issues and works around obstacles without waiting for direction

For candidates based in Ontario, the pay range for this position at the start of employment is expected to be between CA$125,280 and CA$235,736/year with an expected On Target Earnings (OTE) between CA$139,200 and CA$258,000/year (including bonus or commission). Your exact offer may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. In addition to cash compensation, this role qualifies for a comprehensive Total Rewards package that includes equity grants of restricted stock (RSUs) so that you will own a piece of our company.

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 this role

As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale.  This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses.

What You Will Do

• Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance
• Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability
• Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns
• Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow
• Optimize performance, reliability, and cost of the ML platform
• Evaluate and integrate emerging Databricks features
• Stay ahead of the curve by engaging with the latest developments in machine learning and AI
• Serve as senior ML technical advisor to Faire’s data science and production engineering teams 
• Represent Faire at ML conferences and meetups
• Mentor ML engineers and raise the overall bar for Machine Learning at Faire

What it takes

• 10-12 years of experience building and improving large-scale ML or data platforms.
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field.
• Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization
• Proven ability to design systems that support multiple data science teams and production workloads
• Strong background in distributed systems, ML infrastructure, and cloud architecture.
• Demonstrated technical leadership across teams and orgs; ability to influence without authority
• Experience integrating LLM workflows into enterprise platforms is a plus
• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

Canada: the pay range for this role is $248,000 to $341,000 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

About this role

As the Senior Staff Machine Learning Platform Engineer, you will own the technical vision and evolution of Faire’s ML platform. You will set standards, influence org-wide architecture, and lead complex, cross-functional initiatives that unlock data science velocity at scale.  This role will also be key to adapting ML workflows to take advantage of modern AI productivity tools. You won’t just build models, you will architect the systems that allow those models to help tens of thousands of small retailers compete and grow their local businesses.

What You Will Do

• Define and drive the long-term architecture of Faire’s ML platform including training, inference, feature management, governance
• Establish company-wide standards for code quality, testing, MLOps (CI/CD), experimentation, model lifecycle management, and observability
• Lead adoption and advanced use of Unity Catalog, multi-workspace strategies, and data/ML mesh patterns
• Architect highly scalable ML workflows using Spark, Delta Lake, and MLflow
• Optimize performance, reliability, and cost of the ML platform
• Evaluate and integrate emerging Databricks features
• Stay ahead of the curve by engaging with the latest developments in machine learning and AI
• Serve as senior ML technical advisor to Faire’s data science and production engineering teams 
• Represent Faire at ML conferences and meetups
• Mentor ML engineers and raise the overall bar for Machine Learning at Faire

What it takes

• 10-12 years of experience building and improving large-scale ML or data platforms.
• A degree (preferably graduate level) in Computer Science, Engineering, Statistics, or a related technical field.
• Deep expertise in Databricks lakehouse architecture, including governance via Unity catalog, orchestration via Workflows, and cost optimization
• Proven ability to design systems that support multiple data science teams and production workloads
• Strong background in distributed systems, ML infrastructure, and cloud architecture.
• Demonstrated technical leadership across teams and orgs; ability to influence without authority
• Experience integrating LLM workflows into enterprise platforms is a plus
• Previous contributions to open source ML Infrastructure projects or research publications is a very strong plus

Tech Stack

Faire uses a modern cloud based tech stack.  For this role, you’ll want to be proficient with the following:

Salary Range

San Francisco: the pay range for this role is $295,000 to $405,500 per year. 

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

Faire uses Artificial Intelligence (AI) to screen and select applicants for this position.

This job posting is for an existing vacancy.

Key Responsibilities

Skills, Knowledge and Expertise

Preferred Skills

About this role

As a Senior Applied AI/ML Scientist on the Search ranking team, you will help shape the technical vision, machine-learning algorithm strategy, and system design behind one of our most important growth levers: Search (the primary tool used by customers on any e-commerce site). You will advance real-time search and recommendation systems that power next-generation shopping experiences.

You’ll work at the frontier of algorithms, combining query understanding, deep learning, transformer-based sequential modeling, graph neural networks, and structured behavioral data to return hyper-relevant, personalized products and brands for every user query.

This is a rare chance to influence the end-to-end personalized discovery experience at Faire within a high-scale, deeply multi-modal environment, while collaborating closely with a talented team of scientists and engineers.

What you'll do

• Build our next-generation Search ranking algorithms by integrating the latest advances in deep learning and machine learning to personalize the retailer discovery journey at Faire
• Leverage LLM to extract multimodal signals (text, visual) to better profile users and their intents. 
• Partner closely with teams across Faire to experiment and improve the ML models for search ranking and beyond.
• Design and productionize natural-language search and discovery systems so that intelligent agents can generate relevant and personalized collections, explain search results, and assist retailers with browsing, filtering, and evaluation.
• Share best practices regarding deep learning model development, agent-workflow evaluation, and MLOps, and help teammates level up through code reviews and technical guidance.

You're a great fit if you have...

• 5+ years of industry experience building large-scale ML models with business impact and shipping ML solutions to production, including 3+ years in search, recommendation, or ads ranking
• A Master’s or PhD in Computer Science, Statistics, or a related STEM field.
• Strong programming skills (Python, Java, or equivalent) and hands-on experience with deep-learning libraries (e.g., PyTorch) and big data technologies (e.g., Spark).
• Deep understanding of machine learning best practices (e.g., training/serving, imbalanced data, A/B testing, feature engineering, and feature/model selection) and algorithms (e.g., user modeling, deep learning, and reinforcement learning) with applications in search, recommendation, and advertising domains.
• A product-focused mindset and a bias toward execution—moving quickly from research papers to prototypes and production.
• Excellent written and verbal communication skills and strong cross-functional influence that raise the technical bar beyond your immediate team.

Bonus points for...

• Contributions to open-source ML libraries or peer-reviewed publications in ML/AI.
• Industry experience developing and productizing LLM-based applications and systems in the search domain.
• Industry experience building search and recommendation systems for e-commerce or two-sided marketplaces.
• Experience using AI tools (e.g., Cursor, Claude Code, Codex) for code development and daily productivity.
• Familiarity with Kotlin

Salary Range

California: the pay range for this role is $192,000 to $264,000 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

About the Role

Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement

As a Senior Data Engineer, you will manage the "discovery-to-scale" pipeline, identifying recurring patterns in the field and handing off validated solutions to Platform Engineers for enterprise generalization. In this forward-deployed role, you will bridge the gap between building technical products and solving real-world business problems through rapid solution delivery and deep domain immersion. Your primary objective is to design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities.

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact.
• Enterprise Data Integration & Architecture: Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT). Must demonstrate the ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data.
• Cloud-Native Data Ecosystems: Deep expertise in deploying and managing data infrastructure on cloud platforms (AWS, Azure, or GCP). Proficient in Infrastructure as Code (Terraform/CloudFormation) and establishing end-to-end CI/CD pipelines for data solutions.
• Advanced Data Modeling: Strong skills in conceptual, logical, and physical data modeling, with the ability to balance data normalization, query performance, and safely manage complex schema migrations in production.
• AI/MLOps Readiness: Mastery of incorporating AI tools to optimize data engineering workflows and the ability to design data validation and evaluation frameworks that support the deployment and governance of AI/ML models.
• Full-Stack Solution Delivery: Capability to rapidly prototype and build complete, end-to-end data applications across diverse technology stacks, prioritizing solution speed and business value while effectively managing technical debt.
• System Reliability & Resilience (SRE): Direct experience defining and monitoring service level objectives (SLOs/SLIs). A track record of designing highly resilient data systems that ensure graceful degradation and driving post-incident improvements.
• Architectural Leadership: Ability to make sound architectural trade-offs, design scalable system components, and produce high-quality, well-tested code that adheres to enterprise standards.

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model

About the Role

Join forces with Appnovation to deliver high-impact results for one of our key strategic partners - a global leader in their field. This engagement offers a unique vantage point into a world-class organization with exceptional opportunities for professional growth and long-term career advancement

As a Senior Data Engineer, you will manage the "discovery-to-scale" pipeline, identifying recurring patterns in the field and handing off validated solutions to Platform Engineers for enterprise generalization. In this forward-deployed role, you will bridge the gap between building technical products and solving real-world business problems through rapid solution delivery and deep domain immersion. Your primary objective is to design and build data integration, storage systems, and infrastructure that enable analytics and AI capabilities.

This role requires high-level autonomy, where you will define your own direction within strategic goals, influence multiple teams, and navigate high complexity and ambiguity to deliver tangible business results.

What we are looking for

• Experience & Education: Bachelor's degree in Computer Science or Engineering with 8–12 years of relevant experience leading and delivering complex data engineering projects with multi-team or business impact.
• Enterprise Data Integration & Architecture: Proven expertise in designing, building, and maintaining robust, scalable data pipelines (ETL/ELT). Must demonstrate the ability to navigate complex enterprise data landscapes, effectively handle undocumented schemas, and implement resilient integration solutions for high-volume data.
• Cloud-Native Data Ecosystems: Deep expertise in deploying and managing data infrastructure on cloud platforms (AWS, Azure, or GCP). Proficient in Infrastructure as Code (Terraform/CloudFormation) and establishing end-to-end CI/CD pipelines for data solutions.
• Advanced Data Modeling: Strong skills in conceptual, logical, and physical data modeling, with the ability to balance data normalization, query performance, and safely manage complex schema migrations in production.
• AI/MLOps Readiness: Mastery of incorporating AI tools to optimize data engineering workflows and the ability to design data validation and evaluation frameworks that support the deployment and governance of AI/ML models.
• Full-Stack Solution Delivery: Capability to rapidly prototype and build complete, end-to-end data applications across diverse technology stacks, prioritizing solution speed and business value while effectively managing technical debt.
• System Reliability & Resilience (SRE): Direct experience defining and monitoring service level objectives (SLOs/SLIs). A track record of designing highly resilient data systems that ensure graceful degradation and driving post-incident improvements.
• Architectural Leadership: Ability to make sound architectural trade-offs, design scalable system components, and produce high-quality, well-tested code that adheres to enterprise standards.

Who you are

• Polymath Oriented: You bridge gaps between engineering, design, business, and science, rapidly immersing yourself in new domains to speak the language of the business.
• Curious Explorer: You seek out ambiguity rather than avoiding it, driving team curiosity through challenging questions and creating an environment that encourages experimentation.
• Outcome Owner: You drive an accountability culture focused on business impact rather than just deliverables, owning relationships and making trade-offs between custom solutions and generalizable work.
• Systems Thinker: You map complex system interactions across technical and business domains, anticipating cascading effects and understanding how technology changes impact operations.
• Precise Communicator: You translate seamlessly between technical and business language, ensuring requirements are clear enough to enable AI generation and facilitate productive discussions with stakeholders.
• Problem Discoverer: You embed with users to discover latent needs, turning ambiguity into clear problem statements rather than waiting for defined tasks.

What Appnovation Offers 

• Challenging and rewarding work with real impact
• Direct Access to Cutting-Edge AI Platforms
• Diverse and Inclusive Culture 
• Growth opportunities for personal and professional development
• A collaborative and innovative work environment where your ideas are valued
• Exposure to exciting projects and high-profile clients
• Supportive work environment with access to company leaders
• Hybrid working model

We are seeking a seasoned Technical Leader to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.

We are seeking a seasoned Software Engineer to build and scale the foundational compute infrastructure that powers our state-of-the-art AI models—from multimodal training data pipelines to high-throughput, low-latency video generation.

Responsibilities

You will be the core engineer responsible for building the robust, efficient, and scalable platform that enables our research and production teams to rapidly iterate on HeyGen's generative video models. Your contributions will directly impact model performance, developer productivity, and the final quality of every AI-generated video.

• Optimize GPU Utilization: Design and implement mechanisms to aggressively optimize GPU and cluster utilization across thousands of devices for inference, training, data processing and large-scale deployment of our state-of-art video generation models.

• Develop Large-Scale AI Job Framework: Build highly scalable, reliable frameworks for launching and managing massive, heterogeneous compute jobs, including multi-modal high-volume data ingestion/processing, distributed model training, and continuous evaluation/benchmarking.

• Enhance Observability: Develop world-class observability, tracing, and visualization tools for our compute cluster to ensure reliability, diagnose performance bottlenecks (e.g., memory, bandwidth, communication).

• Accelerate Pipelines: Collaborate closely with AI researchers and AI engineers to integrate innovative acceleration techniques (e.g., custom CUDA kernels, distributed training libraries) into production-ready, scalable training and inference pipelines.

• Infrastructure Management: Champion the adoption and optimization of modern cloud and container technologies (Kubernetes, Ray) for elastic, cost-efficient scaling of our distributed systems.

Minimum Requirements

We are looking for a highly motivated engineer with deep experience operating and optimizing AI infrastructure at scale.

• Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

• 5+ years of full-time industry experience in large-scale MLOps, AI infrastructure, or HPC systems.

• Experience with data frameworks and standards like Ray, Apache Spark, LanceDB

• Strong proficiency in Python and a high-performance language such as C++  for developing core infrastructure components.

• Deep understanding and hands-on experience with modern orchestration and distributed computing frameworks such as Kubernetes and Ray.

• Experience with core ML frameworks such as PyTorch, TensorFlow, or JAX.

Preferred Qualifications

• Master's or PhD in Computer Science or a related technical field.

• Demonstrated Tech Lead experience, driving projects from conceptual design through to production deployment across cross-functional teams.

• Prior experience building infrastructure specifically for Generative AI models (e.g., diffusion models, GANs, or large language models) where cost and latency are critical.

• Proven background in building and operating large-scale data infrastructure (e.g., Ray, Apache Spark) to manage petabytes of multi-modal data (video, audio, text).

• Expertise in GPU acceleration and deep familiarity with low-level compute programming, including CUDA, NCCL, or similar technologies for efficient inter-GPU communication.

What HeyGen Offers

• Competitive salary and benefits package.
• Dynamic and inclusive work environment.
• Opportunities for professional growth and advancement.
• Collaborative culture that values innovation and creativity.
• Access to the latest technologies and tools.

HeyGen is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.