This is Engineering at Lattice

Lattice’s Engineering team is continuously working to better both our product and our craft. We use a modern, cutting-edge tech stack and love experimenting with new technologies. We strive for maintainable, robust, and performant code. We’re highly collaborative and continuously iterative and work closely with designers and product managers. We prioritize not only great technical architecture but also an amazing product experience.

As a Data Platform Engineer, you will play a pivotal role in designing and maturing Lattice’s centralized data platform — starting with a modern data lakehouse built on AWS. This is an opportunity to be a founding member of a new team, build the backbone of our data ecosystem, and directly influence the intelligence and interconnectedness of our products.

You will architect and implement foundational data infrastructure that enables scalable storage, reliable data processing, and secure access across the organization. In addition to building the lakehouse itself, you will design and maintain a set of reusable connection and query utilities that empower internal stakeholders to interact with the platform efficiently and safely.

What You Will Do

• Standardize Lattice’s data infrastructure and practices through establishing a simple, cohesive, and reliable platform that seamlessly integrates internal and partner data
• Design, develop, and deploy scalable data pipelines that can ingest, process, and serve data across multiple teams for batch and streaming workloads.
• Make data effortlessly accessible – abstract infrastructure complexity through reusable SDKs, libraries, and tooling
• Shape data governance practices ensuring access to data is secure, compliant, and high-quality. 
• Partner with Engineering, Product, and business leaders to identify data needs and implement solutions that align with strategic objectives.

What You Will Bring to the Table

• 2+ years of experience in software, data, or analytics engineering with exposure to a centralized “data platform” or large-scale data infrastructure project.
• Fluency in SQL and a general purpose programming language; Python or TypeScript preferred
• Familiarity with a data warehouse/lakehouse platform e.g. Snowflake, Redshift, BigQuery, Databricks
• Familiarity with AWS services or their equivalents e.g. IAM, Glue, Lambda, Athena, Redshift, Kinesis, EKS
• Nice to have: Hands-on experience with data processing frameworks like dbt, Spark, Kafka Streams, or Flink
• Willingness to learn and curiosity into how trustworthy, insightful data can unlock value for our users

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 incentive 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

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

The Support Experience engineering organization builds and improves Stripe’s user support from end to end: how users get help within our products, how they get in touch with us when they have questions, and how our teams use internal tools to answer those questions. We’re accountable for the quality and reliability of this support stack and we use data and firsthand user research to continuously improve it. 

Providing great support to users of all sizes is culturally important to everyone at Stripe. We are a group of friendly, user-oriented engineers that partner closely with Stripe’s world-class design, product, and operational teams. This includes the external-facing support interfaces (support.stripe.com), content, entry points, internal tooling, case routing, and helping product teams across the company reduce support volume by improving our products. We are also using the latest generative AI technologies to re-imagine support experiences, and are developing AI assistants for Stripe’s users and internally to help our operations teams be more productive.

What you’ll do

As a Machine Learning Engineer on the Support Experience team, you'll play a crucial role in enhancing our self-serve support experiences. You will be responsible for designing, building, training, evaluating, deploying, and owning ML models in production. For example, we apply LLMs to answer user questions with conversational agents and personalize product documentation, and are building automated systems to solve complex user problems. You will work closely with software engineers, machine learning engineers, product managers, and data scientists to operate Stripe’s ML powered systems, features, and products. You will also have the opportunity to contribute to and influence ML architecture at Stripe and be a part of a larger ML community. 

Responsibilities

• Design  and implement state-of-the-art ML models and large scale ML systems for enhancing self-serve support capabilities, balancing ML principles, domain knowledge, and engineering constraints
• Develop and optimize contextual conversation models and ML-powered resolution flows for common support scenarios, using tools such as PyTorch, TensorFlow, and XGBoost
• Create and refine pipelines for training and evaluating models in both offline and online environments, with a focus on improving support quality and user satisfaction
• Implement ML features that streamline information collection and processing for support agents, enhancing overall support efficiency
• Collaborate with product, strategy, and content teams to propose, prioritize, and implement new AI-driven support features and improve answer capabilities
• Stay current with the latest developments in ML/AI, particularly in natural language processing and conversational AI, and apply innovative ideas to improve support experiences

Who you are

We are looking for ML Engineers who are passionate about building ML systems that touch the lives of millions. You have experience developing efficient feature pipelines, building advanced ML models, and deploying them to production. You are comfortable with ambiguity, love to take initiative, have a bias towards action, and thrive in a collaborative environment.

Minimum requirements

• Bachelor's Degree in ML/AI or related field (e.g. math, physics, statistics)
• 3+ years in AI/ML and backend engineering, including building and operating production ML systems at global scale with stringent SLOs—balancing reliability, latency, and cost—with privacy, security, and compliance by design.
• Deep and up-to-date applied LLM experience: RAG/embeddings, tool use/function calling, agentic planning/orchestration architectures, post-training methods, code generation, benchmarks and evaluations, etc. Familiarity with classical ML methods and common frameworks e.g. Pytorch, TensorFlow.
• Proficient in Python; strong distributed systems and data science fundamentals.
• Experience working closely with product management, design, other engineers, and other cross-functional partners.
• Strong technical leadership and communication: mentoring and elevating engineers, elevating AI/ML awareness and posture within organizations, setting architectural direction, and driving alignment in ambiguity.

Preferred qualifications

• MS/PhD degree in ML/AI or related field (e.g. math, physics, statistics)
• Experience working in Java or Ruby codebases
• Experience designing, deploying, and owning Agentic LLM solutions (e.g., multi-step orchestrators, tool use/function calling) specifically for complex customer support or internal workflow automation.
• Comfortable working with distributed teams across multiple locations and time zones

Role Summary

We’re looking for a Digital Content & AI Automation Manager to lead our transition to 'Vibe Marketing.' Inspired by the shift toward Vibe Coding, we want to bridge the gap between creative intent and digital execution. You’ll move Okta away from manual tickets and rigid CMS forms toward an agentic, self-service model—building the tools that allow marketers to describe a goal in natural language and see it manifest across our digital ecosystem.

This is a test, learn, build, iterate role. You aren't just managing a stack; you’re building an autonomous engine that empowers every marketer to be a creator.

What You’ll Actually Do

• Build the "Vibe Marketing" tools: Create the workflows and agentic layers that allow non-technical stakeholders to manage and scale digital content across its entire lifecycle using natural language and AI assistance.
• Develop Agentic Support Models: Prototype and deploy AI agents that act as "co-pilots" for Marketing Managers—handling everything from automated tagging and metadata to complex distribution across our headless ecosystem.
• Architect Self-Service Systems: Reduce the "time-to-live" by building modular, reusable content structures that agents can manipulate, moving us beyond the constraints of traditional platforms like Adobe Experience Manager.
• Operate Like a Lab: Run rapid experiments with emerging AI tools and automation platforms. Build scrappy prototypes—not just strategy decks—to prove that "vibe-based" creation works at enterprise scale.
• Partner Across Teams: Bridge the gap between "what if" and "here’s how," working with Marketing, Engineering, and Digital teams to turn agentic concepts into production-ready workflows.

What We’re Looking For

• The "Vibe" Mindset: You understand the shift from "doing the work" to "directing the agents." You’ve followed the Vibe Coding movement and are itching to apply it to Marketing Tech.
• 4–8 Years of Experience: You’ve seen the limitations of legacy CMS architectures and are ready to bypass those bottlenecks by building a modern, agent-led content supply chain.
• Hands-on AI & Automation: You don't just prompt; you build. You have experience with APIs, MCP, LLM orchestration, and connecting tools to create seamless loops.
• Technical Fluency: You aren't a full-stack engineer, but you understand how to navigate enterprise complexity—you're comfortable with structured content, and the logic of how data flows between a headless CMS, an LLM, and the front-end.

#LI - Hybrid

P24086_3333054

Influencer and Content Creator Strategist (Contract) 

Toronto, Canada, hybrid (preferred) 

East Coast, remote  (considered)

*Please note, this is a temporary position, expected to last 12-18 months. This role has a hybrid ​​schedule, with a minimum of one day per week on-site and additional in-office days as needed, needing the candidate to be within driving distance of the SIE office in Toronto. Will consider East Coast based remote candidates. We aim to provide flexibility while ensuring the support and collaboration essential to our team’s success. Applications from fully remote candidates will still be considered.

The Influencer and Content Creator Strategist will lead influencer initiatives in Canada—owning both high-impact paid creator partnerships and the ongoing PlayStation creator/talent partnership program. As a key member of the Global Communications and Canadian Marketing team, this role is responsible for developing and executing influencer strategies that support brand and campaign objectives. Your mission is to create cultural impact and measurable excitement around game and product launches by partnering with creators who authentically move the gaming community—then turning those partnerships into best-in-class content moments across platforms like YouTube, TikTok, Twitch, Instagram, Facebook, and X (Twitter). The individual will oversee strategic planning, day-to-day program management, global content alignment, local content development, and performance reporting and analysis.

The ideal candidate brings strong experience in influencer marketing and relationship management across both paid and earned programs. They possess excellent organizational and communication skills, strong attention to detail, and the ability to manage multiple priorities in a fast-paced, collaborative environment. This person should also be comfortable stepping into an established program and ensuring continuity, operational efficiency, and sustained momentum throughout the duration of the contract.

The successful candidate will be a natural relationship builder with a proven track record of managing influencer and player relationships while supporting integrated marketing campaigns.

Responsibilities include:

 Influencers and Content Creation management

●      Own the Canada creator/influencer strategy across the launch calendar, ensuring creator activity ladders to clear campaign objectives (awareness, excitement, cultural conversation, community engagement) and fits the realities of gaming communities

●      Lead paid influencer partnerships end-to-end with agency support: creator sourcing and evaluation, outreach, negotiation, contracting, briefing, deliverable management, approvals, and post-campaign reporting.

●      Develop creator campaign briefs that translate campaign strategy into creator-native storytelling (what to say, what to show, what to avoid), and ensure creators clearly understand product positioning and key beats.

●      Partner with Social, PR/Comms, Local Campaign Managers and Global PlayStation teams to integrate creators into broader campaigns and community moments.

●      Coordinate creator “capture plans” and access moments (e.g., content days, livestream plans, behind-the-scenes access, event activations) and provide on-site/on-set support when required to ensure optimal content capture and creator experience.

●      Stay ahead of creator platform trends, emerging voices, and cultural moments in Canada, proactively identifying opportunities where PlayStation can show up with relevance.

●      Run and grow the PlayStation creator and talent partnership program in Canada: recruiting and onboarding creators, tiering/relationship management, ongoing communications, community touchpoints, and program operating rhythms

●      Identify, build, and maintain relationships with key influencers, content creators, and power users, evaluating the impact of these partnerships on an on-going basis.

●      Develop and implement content creator tactics for key software and brand campaigns, collaborating closely with the Global Marketing Talent Partnerships team.

●      Create and define an always-on engagement strategy.

●      Ensure top-tier influencers are informed about upcoming feature and product launches, major content updates, and key announcements.

●      Define and report performance measurement for creator work (reach, views/watch time, engagement quality, sentiment, share of conversation, community growth signals), and translate results into actionable recommendations for future launches.

●      Establish metrics to grow and engage the content creator community; regularly analyze sentiment and performance data and adjust strategies accordingly.

●      Own creator/influencer governance and operational hygiene: creator database management, documentation of learnings, and consistent sharing of best practices across teams.

●      Manage budgets for creator partnership fees, in-kinds exchanges and productions in Canada, including forecasting, tracking, and post-mortems that connect spend to outcomes.

●      Foster positive and supportive conversations with content creators around content opportunities, contests, and initiatives relevant to the player community.

●      Distribute player surveys and collect feedback from core players on a regular basis.

●      Build and maintain strong relationships with key community leaders to better understand community needs and insights.

●      Protect PlayStation brand and community trust by setting clear creator standards: brand safety, inclusion, community conduct expectations, and Local Canadian disclosure compliance.

Administration:

●      Manage budgets and timelines for influencer and content creator initiatives, working with agencies to identify and vet the right influencers and ensure content is delivered on schedule for local and global review as needed.

●      Define and manage campaign budgets, thoroughly reviewing proposed spend prior to approval and ensuring all activities remain within agreed financial parameters.

●      Oversee monthly budget forecasting and financial administration related to influencer and content creation programs.

●      Monitor social sentiment and consumer reactions to announcements, capturing key insights, and sharing findings with partners across SIE territories and global teams.

●      Deliver comprehensive post-launch evaluations summarizing performance, insights, results against key metrics, and actionable learnings.

Qualifications:

●      Bachelor’s degree or equivalent

●      5+ years of experience in influencer marketing, partnerships, or creator programs, ideally working with consumer-facing brands or products.

●      Proven creator/influencer experience with end-to-end ownership of paid partnerships (strategy → talent selection → negotiation/contracts → execution → reporting)

●      Demonstrated ability to lead agency partners and talent-driven content productions (creative development, production planning, approvals, timelines, budgets)

●      Exceptional briefing and storytelling ability: can translate a launch strategy into authentic creator-native content moments.

●      Deep fluency in gaming culture and creator ecosystems, including how gamers discover, discuss, and adopt new games/products across social platforms.

●      Strong creator judgment: ability to spot culturally relevant talent early, assess authenticity/fit, and anticipate community reaction

●      Strong communication skills, including written, verbal, and interpersonal communication.

●      Passion for gaming and community building.

●      Deep understanding of the digital, social, and media landscape, with the ability to identify and interpret emerging digital trends.

●      Proven ability to work independently, demonstrate creativity, strong attention to detail, and the ability to manage multiple projects simultaneously.

●      Familiarity with major content creator platforms, including YouTube, Facebook, TikTok, Instagram, and Twitch.

●      Experience developing and managing creator-led initiatives such as giveaways, contests, and community engagement programs.

●      Understanding of mobile gaming, free-to-play models, or live-service operations is a strong plus.

●      Strong project management skills with the ability to prioritize tasks and manage multiple initiatives effectively.

●      Data-literate: comfortable defining success metrics, reading creator performance signals, and using insights to optimize strategy

●      High integrity and compliance mindset, including understanding of disclosure requirements and brand safety expectations in Canada and globally

●      English required; French Canadian language proficiency is a plus.

●      Proficiency with collaboration and productivity tools such as Microsoft Office Suite, Google Workspace, Slack, and AI tools (e.g., ChatGPT, Copilot).

This posting reflects an active, existing opportunity at Sony Interactive Entertainment, and we’re excited to connect with candidates interested in joining our team. This is a contract position expected to last 12-18 months.   

As part of our recruitment process, we may use technology, including artificial intelligence, to support the review of applications and identify candidates whose experience aligns with the requirements of the role. All decisions are made by our hiring team, and these tools are used to support, not replace, human judgment.

We value diverse experiences and do not require prior Canadian work experience for this role.

Your role
As an analytics engineer, you’ll be an integral part of our data analysis and QA team, providing essential data support for our cutting-edge Agentic AI initiatives, specifically with ASR and NLP teams. A key focus will be on leveraging data analysis to identify and drive optimization of the conversational flows and underlying data infrastructure for agentic voice and chat solutions. You will actively seek opportunities to improve the team’s productivity and workflow through automation and process optimization, including implementing automated QA for our agentic systems.

This position reports to the manager of the Data Analysis and QA team and has the opportunity to be based in our Vancouver, Canada Office.

What you’ll do 

• You will work closely with other Agentic AI teams to test and evaluate our Agentic voice and chat solutions.
• You will design and implement data logging and monitoring strategies to capture key analytical insights.
• You will utilize data analysis to identify areas for optimization in the voice bot's conversational flows and data pipeline.
• You will build and maintain data pipelines on Vertex AI pipelines. 
• You will work closely with the AI Platform team to build tooling for data science projects. 
• You will implement automation and processes to improve our workflow. 
• You will create and maintain dashboards (Tableau) and data pipelines (Dataform) that help drive product and business decisions.
• You will contribute to our continuous efforts to enforce data privacy and compliance. 
• You will collaborate with cross-functional teams, including AI, engineering, and product teams.

Skills you’ll bring 

• Bachelor's or Master’s degree in Computer Science, Software Engineering, or related fields.
• 1 - 3 years of working experience with software engineering or data engineering projects. 
• 1 - 3 years of experience with Python, working with GCP, including storage, BigQuery, Compute, Kubernetes, or similar.
• 1 - 3 years of experience with SQL, able to optimize complex SQL queries and build data pipelines. 
• Experience with BI tools such as Tableau. 
• Experience analyzing the performance of conversational AI systems (e.g., voice bots, chatbots) and collaborating with cross-functional teams (AI, Product) on data-driven improvements.
• Experience working with popular LLM frameworks.
• Strong problem-solving and analytical abilities, with the capacity to handle complex technical and analytical problems.

Narvar is Growing! We’re building Navi — Narvar’s agentic AI that automates post-purchase resolution for the world’s leading retailers. Hundreds of millions of consumers interact with Narvar every year. Navi is our agentic AI that resolves delivery issues, returns, and refunds through natural conversation — powered by IRIS and 74 billion consumer touchpoints. 

We're looking for senior AI engineers to own this system end-to-end: architecture, model selection, production operations. You'll help decide what gets built and how.

Day-to-day

• Design and build conversational AI agents for returns, claims, and customer service experiences
• Own agent systems from architecture → implementation → evaluation → production operations
• Build RAG / context graph retrieval pipelines that ground agent responses in real company and customer data
• Design agent orchestration for multi-step workflows that interact with identity, risk, order, and loyalty systems
• Create evaluation frameworks to measure task completion, accuracy, safety, and user satisfaction
• Implement guardrails and safety mechanisms — content moderation, hallucination detection, graceful fallbacks
• Integrate conversational experiences across web, mobile, SMS, and email channels
• Make real decisions around prompt design, model selection, latency/cost/quality tradeoffs, and failure modes
• Collaborate with product, design, and ML teams to build systems that are technically sound and product-aware

What We’re Looking For

We care more about judgment and ownership than credentials.

You’re likely a strong fit if you:

• Have shipped conversational AI or agent-based systems used by real users in production
• Have built production systems on top of LLM APIs and agent frameworks — not just prompt playgrounds, but real integrations involving tool orchestration, context management, and reliability at scale
• Have a point of view on model selection tradeoffs — when to use frontier APIs vs. open-weight models (Qwen, Llama, Mistral), and understand the cost, latency, privacy, and capability tradeoffs of each
• Understand prompt engineering beyond basics: structured outputs, few-shot learning, chain-of-thought, tool calling
• Have built context graph pipelines that go beyond naive retrieval — entity resolution, relationship modeling, and dynamic context assembly from structured and unstructured data
• Have designed agent architectures that use function calling, tool execution, or multi-step reasoning
• Have strong programming skills in Python or TypeScript
• Have experience building and integrating APIs and backend services
• Are comfortable reasoning about evaluation, safety, and reliability in non-deterministic systems
• Take initiative naturally and are comfortable operating with ambiguity

Bonus points

These aren’t hard requirements, but strong indicators:

• You’ve worked in startup or high-ownership environments
• You’ve built and operated AI systems in production, including monitoring and incident response
• You’ve evaluated and iterated on LLM systems for accuracy, hallucination, latency, and cost
• You’ve built or integrated MCP servers or similar tool-use infrastructure
• You’ve influenced technical direction by earning trust, not by mandate
• You use modern tooling (including AI-assisted development workflows) to increase leverage, not outsource thinking

(Note: we care about outcome and judgment, not how flashy your tools are.)

Why AI at Narvar?

Because post-purchase is one of the highest-leverage applications of conversational AI.

We’re building AI agents where:

• The problem space is well-defined but complex — returns, claims, and support have clear business logic but messy real-world edge cases
• Scale is real — hundreds of millions of consumer interactions per year across major global retailers
• Impact is measurable — resolution rates, customer satisfaction, cost savings, not vanity metrics
• The work is greenfield — you’re not maintaining a legacy chatbot, you’re building the next generation

You’ll help define where and how AI agents should operate, not just implement someone else’s spec.

Why Narvar ( from an Engineer's perspective?)

• Real scale, real customers, real consequences
• Startup-level ownership with platform-level impact
• Teams that value thinking, judgment, and responsibility
• Low ego, high trust, and room to do your best work

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

Consensys is the leading blockchain and web3 software company founded by Joe Lubin, CEO of Consensys and Co-Founder of Ethereum. Since 2014, Consensys has been at the forefront of innovation, pioneering technological developments within the web3 ecosystem.

Through our product suite, including the MetaMask platform, Infura, Linea, Diligence, and our NFT toolkit Phosphor, we have become the trusted collaborator for users, creators, and developers on their path to build and belong in the world they want to see.

Whether building a dapp, an NFT collection, a portfolio, or a better future, the instinct to build is universal. Consensys inspires and champions the builder instinct in everyone by making web3 universally easy to use and develop on.

Our mission is to unlock the collaborative power of communities by making the decentralized web universally easy to access, use, and build on. 

You’ll get to work on the tools, infrastructure, and apps that scale these platforms to onboard one billion participants and 5 million developers. You’ll be constantly exposed to new concepts, ideas, and frameworks from your peers, and as you work on different projects — challenging you to stay at the top of your game. You’ll join a network of builders that reaches the edge of our ecosystem. Consensys alumni have moved on to become tech entrepreneurs, CEOs, and team leads at tech companies. 

About the Design Team

MetaMask's design team aims to establish MetaMask as the premier wallet in fintech, elevating the craft of design and leading the industry as the next phase of decentralized finance unfolds. Our goal is to reduce friction while preserving user trust, so more people can safely explore the world of Web3.

What you’ll do

MetaMask is used by millions of people as their gateway to web3. As the product grows, so does the need for experiences that feel clear, responsive, and human. Motion plays a big role in that.

We’re looking for a Staff Motion Designer to join our Design Systems team. In this role, you’ll shape how motion shows up across MetaMask—from small interaction details to larger moments of expression. A core part of the work is defining a shared motion language and building systems that help teams use it consistently across the product.

This role sits within the design system, but it’s not just about documentation. You’ll be making things—prototyping, exploring, refining—and working closely with designers and engineers to bring motion into the product in a way that scales.

What you’ll work on

• Use motion to make the product easier to understand—helping people see what’s happening, what changed, and what to do next
• Define a clear, shared motion language for MetaMask—how things move, respond, and feel across surfaces
• Build patterns, guidelines, and reusable assets that allow motion to scale across teams and platforms
• Introduce moments of delight where they add value, without getting in the way
• Partner with product designers and engineers to bring motion into the product in a way that feels natural and performs well
• Use prototypes to explore and communicate interaction ideas
• Contribute to the overall level of craft across the team through feedback and collaboration

Would be great if you brought this to the role

• You’ve spent 6+ years working with motion in digital products, using animation and interaction to make complex experiences easier to understand
• You define motion languages and patterns that create consistency across screens, features, and platforms
• You build scalable systems—guidelines, reusable assets, or components—that help teams apply motion without starting from scratch
• You work closely with engineers to bring motion into production in ways that feel smooth, perform well, and hold up across platforms
• You use prototyping to explore and communicate ideas, helping teams align on how things should move and respond
• You balance clarity and delight, knowing when motion helps guide someone and when it might get in the way
• You raise the bar for craft, through feedback, collaboration, and hands-on contribution

Don't meet all the requirements? Don't sweat it. We’re passionate about building a diverse team of humans and as such, if you think you've got what it takes for our chaotic-but-fun, remote-friendly, start-up environment—apply anyway, detailing your relevant transferable skills in your cover letter. While we have a pretty good idea of what we need, we're ready for you to challenge our thinking on who needs to be in this role.

It is a requirement of employment in this position that applicants will be required to submit to background checks including but not limited to employment, education and criminal record checks. Further details will be provided to applicants that successfully meet the criteria for the position as determined by the company in its sole discretion. By submitting an application for employment, you are acknowledging and consenting to this requirement.

About the role:

Samsara’s Core GTM Programs team enables a high-performance go-to-market organization by leveraging technology, automation, and best-in-class methodologies to streamline operations, improve forecasting accuracy, and maximize efficiency & effectiveness across Sales, Customer Success, and related functions.

Within this team, the CS Core Programs PMO plays a critical role in driving the operating rhythm and execution of Samsara’s Customer Success organization. As a Senior Program Manager I, you will lead and deliver large-scale, cross-functional programs that support strategic CS priorities, including, retention and risk reviews, cross-functional alignment and operational scalability.

The ideal candidate brings strong analytical and business acumen, a passion for building scalable processes, and a proven track record of leading complex programs in fast-paced environments. This role requires a strong focus on change management, stakeholder alignment, and delivering measurable business impact across the post-sales journey.

We are looking for candidates who will champion, role model, and embed Samsara’s operating principles as we scale globally and across new offices.

This is a remote position open to candidates residing in Canada.

You should apply if:

• You want to impact the industries that run our world: Every phone call you answer and every email you send can affect whether truck drivers deliver goods on time and without accidents, whether students get dropped off safely from school, or whether power gets restored quickly after a natural disaster.
• You thrive the most when solving problems: Our constantly expanding technology and the complexities faced by our customers provide an exciting range of challenges for our GTM teams. With a growth mindset and a desire to learn, you will strategically partner with our customers to find unique solutions to help keep their operations safe, efficient, and sustainable.
• You are a natural relationship builder: Whether the relationship is with our customers or with cross-functional teams in Samsara, you are in constant communication and collaboration with key stakeholders to win as a team.
• You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. This GTM Programs  team is still shaping its future and you will have plenty of autonomy and opportunities to master your craft in a hyper-growth environment.
• You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by the best and brightest professionals out there.

In this role, you will own:

• Program Execution & Operational Cadence: Own and manage core Customer Success cadences, including QBRs, risk reviews, top deal reviews, and internal planning forums, ensuring consistent structure, clear outputs, and strong follow-through.
• Business Reviews & Execution Forums: Drive end-to-end coordination of key CS meetings and execution moments, including blitz days and cross-functional cadences, ensuring alignment, accountability, and high-quality execution.
• Operating Calendar & Planning Rhythm: Build and maintain the CS operating calendar, including planning cycles, key milestones, and recurring forums, to ensure alignment across teams and visibility into priorities.
• Product Release & Readiness Coordination: Partner with Product, Enablement, and CS leadership to manage the new product release calendar, ensuring readiness, communication, and effective rollout to the field.
• Cross-Functional Alignment: Partner closely with Customer Success, Sales, Support, Product, Operations, and Finance to drive clear ownership, communication, and alignment across all core programs.
• Program Measurement & Continuous Improvement: Track program effectiveness through defined KPIs and feedback loops, and continuously improve cadences to drive better execution and customer outcomes.

Minimum requirements for the role:

• Bachelor’s degree from a 4-year institution; MBA a strong plus.
• 6-8 years of experience in program management, sales operations, strategy, or consulting, ideally in a high-growth B2B SaaS environment
• Demonstrated success leading cross-functional GTM programs that improve sales execution and scalability
• Strong program management skills with expertise in end-to-end delivery (i.e. framing the need, scope requirements, document project roadmaps, partnering with teams, defining KPIs and reporting out on results)
• Ability to ramp up quickly on business priorities and derive insights from data to inform decisions
• Strong communication and written language skills including clear and concise documentation
• Proven track record of building trust and effectively partnering with a wide variety of stakeholders: executives, managers, front-line teammates and cross-functional partners 
• Diplomacy, tact, and poise under pressure when working through issues, skilled at having prioritization conversations and discussing tradeoffs 

Ideal Candidate has:

• Experience with B2B hardware and SaaS products 
• PMP certification, Agile/Scrum Certification  
• Experience using AI-powered tools to accelerate program design, automate execution tasks, or surface strategic insights.

ABOUT THE ROLE

We are seeking a highly skilled and intellectually curious analyst to shape the future of financial data at Instacart, driving innovation at the intersection of systems, analytics, and business strategy.

In this role, you will architect and deliver data models, pipelines, and reporting infrastructure that empower Finance and Accounting with trusted insights at scale. 

You’ll collaborate across technical and business teams to ensure financial data is accurate, reliable, and compliant, while also advancing large-scale systems initiatives, accelerating the month-end close, and optimizing cloud spend in our AWS environment.

ABOUT THE TEAM

The Financial Data Analytics team is the connective tissue between Finance, Accounting, and Engineering. Our mission is to deliver trusted financial data that is both a foundation for compliance and a catalyst for strategic decision-making. We combine technical depth with financial expertise to build scalable, high-value data solutions—transforming complexity into clarity and empowering leaders to act with confidence.

KEY RESPONSIBILITIES

• Bridge Data & Business Needs – Translate business requirements into scalable data models by asking the right questions, digging into details, and mining insights that create measurable impact.
• Own Data Initiatives End-to-End – Take ambiguous ideas and transform them into well-defined, high-impact projects with clear deliverables.
• Build Decision-Making Tools – Design and automate dashboards, models, and reporting systems that surface clear insights and guide long-term growth strategies.
• Support Revenue Accounting – Build and maintain data products (dashboards, reports, analyses) that underpin the Revenue Accounting organization, including embedding revenue recognition logic into robust financial data models.
• Ensure Compliance & Governance – Apply compliance-first design principles to support SOX, audit readiness, and enforce data governance standards.
• Maintain Data Integrity – Implement validation, monitoring, and reconciliation frameworks to ensure accuracy, consistency, and reliability across financial datasets.
• Drive Continuous Improvement – Proactively identify opportunities for process optimization, automation, and system enhancement, unlocking efficiency across Finance and Accounting.
• Leverage AI & Next-Generation Analytics – Harness cutting-edge AI technologies (e.g., Claude, Cursor, Python ML libraries, Copilot) to reimagine how financial data is modeled, automated, and delivered—accelerating insights, scaling workflows, and shaping the future of financial analytics.

ABOUT YOU

Minimum Qualifications

• Bachelor’s degree in a related field
• 5+ years (7+ preferred) of experience in data analytics or analytics engineering roles
• Strong SQL and cloud data fundamentals, with hands-on experience in Snowflake, dbt, and BI tools (Mode, Looker, Tableau, etc.)
• Experience building and supporting complex data pipelines with emphasis on accuracy, compliance, and traceability
• Familiarity with financial data structures, accounting processes, and enterprise systems (e.g., Oracle, Workday, Salesforce, Adaptive)
• Strong communication skills with the ability to engage effectively across technical and non-technical teams

Preferred Qualifications

• Public company experience with exposure to SOX compliance
• Background in high-growth technology environments
• Experience implementing large-scale financial or operational systems (ERP, enterprise data platforms, etc.)
• Project management experience a plus
• Demonstrated ability to support Finance and Accounting teams with scalable data solutions
• Cloud cost management experience, ideally in an AWS environment
• Familiarity with AI/ML applications in data analytics (e.g., natural language SQL tools, forecasting models, anomaly detection frameworks)

#LI-Remote

The Customer Success Manager II is responsible for driving long-term success and growth across a strategic portfolio of enterprise customers. This role serves as the primary business partner and trusted advisor to senior stakeholders, ensuring an exceptional customer experience, strong net revenue retention, high product adoption, and advocacy.

As the key point of contact for Diligent’s solutions, the CSM II leads proactive account management, orchestrates cross-functional resources, and partners closely with Sales and Services to deliver measurable outcomes and expand our footprint within each account.

Key Responsibilities

• Own a portfolio of enterprise accounts with accountability for renewal, net revenue retention, and expansion, leveraging data and insights to proactively manage risk and opportunity.
• Drive product adoption and value realization by developing and executing customer success plans aligned to the customer’s strategic objectives and key outcomes.
• Deliver a best-in-class customer experience across all phases of the customer lifecycle, from onboarding through renewal, coordinating with Implementation, Professional Services, Support, Product, and other internal teams.
• Lead executive-level engagements, including QBRs/EBRs and strategic reviews with C-suite, board administrators, and senior directors, to demonstrate ROI, influence adoption, and surface new opportunities.
• Identify, qualify, and partner on expansion opportunities in close collaboration with the Expansion Sales team, ensuring smooth handoffs, aligned account strategies, and clear growth plans.
• Facilitate successful onboarding and rollout of Diligent products and modules, working alongside the Implementation team to ensure stakeholder alignment, training, and effective change management.
• Build and maintain strong, multi-threaded relationships with key business and technical stakeholders, becoming a trusted advisor who understands their governance, risk, compliance, and operational priorities.
• Act as the voice of the customer internally, providing structured feedback and insights to Product, Marketing, Services, and Operations to influence roadmap and process improvements.
• Monitor account health and usage leveraging dashboards and analytics, intervening early to address risks, drive adoption, and reinforce value.
• Champion customer advocacy, by identifying referenceable customers, case study opportunities, testimonials, and participation in user groups or events.
• Collaborate on process and playbook improvements within the Customer Success organization to drive consistency, scalability, and excellence in how we serve enterprise customers.

Required Experience & Skills

• 5+ years of professional experience, including 2–4+ years in Customer Success, Account Management, or a similar client-facing role within B2B SaaS.
• Proven experience managing mid-market and/or enterprise accounts, with comfort engaging senior and executive stakeholders (Director, VP, C‑Suite).
• Demonstrated track record of meeting or exceeding renewal, retention, and expansion targets.
• Strong experience using CRM tools (preferably Salesforce) to manage accounts, opportunities, and customer health activities.
• Excellent communication and presentation skills, able to translate complex concepts into clear, compelling narratives for multiple stakeholder groups.
• Strong consultative and problem-solving skills, with a natural curiosity about the customer’s business, use cases, and success metrics.
• High level of resilience, ownership, and accountability, with the ability to navigate ambiguity and manage competing priorities across a large book of business.
• Passion for technology and a solution-centric mindset, with the ability to quickly learn new products and articulate their business value.
• Strong organizational skills and attention to detail, with experience managing multiple customers, projects, and deadlines simultaneously.

Preferred Qualifications

• Experience in governance, risk, compliance, legal, or adjacent enterprise software environments is a plus.
• Background working in a matrixed, global organization with cross-functional partners across time zones.
• Familiarity with customer success platforms and data-driven approaches to managing account health and adoption.

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.

About the Role:

We are seeking an experienced Principal Software Engineer (Data) to join our fast-paced, collaborative data team. In this role, you will have broad authority to drive the direction of our technographic data services, building world-class data pipelines and systems to process billions of signals and data points. This is an exciting opportunity to solve challenging problems and make a big impact as we invest in making technographics a first-class offering.

What You'll Do:

• Build and optimize big data pipelines to extract and process signals from the web, job postings, and other sources
• Design and implement data architectures and storage solutions to efficiently handle massive data volumes
• Collaborate closely with data scientists to support and integrate ML models into data workflows
• Continuously improve data quality, performance, and scalability of our technographic data platform
• Drive technical strategy and roadmap for the data processing infrastructure.

What We're Looking For:

• Extensive experience building and scaling big data pipelines and architectures from scratch
• Deep expertise in big data frameworks (Hadoop, Spark) and the JVM stack (Java, Scala)
• Strong software engineering fundamentals and ability to write efficient, high-quality code
• Experience with entity recognition and NLP techniques a plus
• Proven track record delivering results and driving projects in a fast-paced environment
• Excellent collaboration and communication skills to work with data scientists, analysts and product teams
• Passion for leveraging huge datasets to power valuable insights.

Ideal Background:

• 10+ years of experience in software engineering roles.
• Experience working with very large datasets and distributed systems
• Familiarity building data pipelines at large tech companies or data-driven organizations
• Bachelor's or advanced degree in Computer Science, Engineering or related technical field.

#LI-SK1

#LI-Remote

Role Description

As a Senior Machine Learning Engineer, you will play a key role in advancing Dropbox’s mission to create a more enlightened way of working. Leveraging cutting-edge AI/ML technologies, you will design, build, deploy, and refine highly reliable AI agents operating at massive scale. Your work will power Dropbox Dash’s universal agentic search and autonomous organization features, transforming how millions of users collaborate, stay organized, and focus on the work that truly matters

Responsibilities

• Design and productionize agentic AI frameworks — including multi-agent coordination, planning, tool-use, and memory — that allow agents to maintain long-term context and execute complex tasks across the Dropbox ecosystem.
• Lead the end-to-end design of ML systems, from fine-tuning (SFT, RLAIF) and advanced prompting to inference optimization and production monitoring.
• Establish rigorous safety, alignment, and evaluation frameworks to ensure our autonomous systems are helpful, honest, and harmless.
• Collaborate across Product, Design, Infra, and Frontend teams to translate ambiguous user needs into concrete AI capabilities that move the needle for the business.
• Mentor junior engineers and serve as a core contributor to the broader Dropbox AI strategy, fostering a culture of technical excellence.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques to improve performance and cost-efficiency.

Compensation

Role Description

Responsibilities

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Many teams at Dropbox run Services with on-call rotations, which entails being available for calls during both core and non-core business hours. If a team has an on-call rotation, all engineers on the team are expected to participate in the rotation as part of their employment. Applicants are encouraged to ask for more details of the rotations to which the applicant is applying.

Requirements

• BS, MS, or PhD in Computer Science, Mathematics, Statistics, or a related quantitative field (or equivalent work experience).
• 8+ years of software engineering experience, with at least 5+ years dedicated to building and deploying production-scale AI/ML systems.
• Professional experience in ML modeling for complex systems such as Search, Ranking, or Recommender Systems.
• Deep familiarity with LLM architectures and hands-on experience with ML libraries (e.g., PyTorch, JAX, or similar).
• Strong proficiency in Python (required) and experience with systems languages like Go or C/C++. You should be comfortable building the infrastructure that surrounds the model.
• Extensive experience working with large-scale distributed data systems and high-throughput production environments.
• Exceptional analytical skills and a "bias to action" when navigating ambiguous technical challenges.

Preferred Qualifications

• PhD with a focus on Deep Learning, NLP, or Reinforcement Learning (RLHF/RLAIF).
• Proven track record of taking AI products from concept to launch, either at a massive scale (millions of users) or by leading multiple 0 → 1 cycles in a fast-paced environment.
• Hands-on experience with autonomous agent frameworks, multi-step planning, tool-use (function calling), and advanced RAG.
• Experience with inference optimization, model distillation, or fine-tuning techniques to improve performance and cost-efficiency.

Compensation

Role Description

The Principal Software Engineer is a highly skilled expert responsible for shaping and executing the organization’s intelligence vision. This role integrates expertise in Artificial Intelligence (AI), Machine Learning (ML), Automation, Data Analytics and Visualization to deliver transformative customer, partner, and colleague experiences that drive revenue growth and enhance productivity.

The position defines the technical direction for intelligence initiatives, leading the design, development, and deployment of robust, scalable, and secure AI solutions while fostering innovation through emerging technologies.

A critical aspect of the role is providing partnership, mentorship and technical guidance, cultivating a culture of excellence and continuous learning. Through close cross-functional collaboration across teams and stakeholders, the role ensures technical efforts are strategically aligned and deliver measurable impact. Additionally, the position plays a central role in strategic problem-solving, addressing complex challenges in intelligence systems and data pipelines, and making informed architectural decisions that ensure long-term scalability and success.

Responsibilities

• Define, drive, and communicate the technical vision for intelligence, AI, and data initiatives, ensuring alignment with CIT strategy, EPD goals, and broader organizational objectives.
• Take a holistic view of CIT systems and architecture to ensure they are scalable, reliable, secure, and maintainable over multiple years.
• Lead the design, development, and deployment of high performance AI systems, data pipelines, and intelligent services from conception through production.
• Make strategic architectural decisions to address complex AI, data, and platform challenges, balancing short term delivery with long term resilience and scalability
• Identify opportunities to simplify systems, reduce operational and security risk, and improve developer productivity.
• Contribute directly to prototyping, proof of concepts, and implementation of technical components when needed to validate strategy, de risk decisions, or accelerate progress.
• Architect, evolve, and scale AI, automation, and intelligence platforms that enable advanced analytics, personalization, search, and intelligent decision making.
• Drive innovation in intelligence models, distributed training, optimization techniques, and data engineering to maximize performance, quality, and business impact.
• Enhance search and discovery capabilities using intelligent algorithms, natural language processing, and modern data systems.
• Evaluate, select, and integrate emerging technologies in AI, ML, and automation to maintain a competitive and forward looking technical posture.
• Partner across engineering, product, design, infrastructure, and other stakeholders to ensure intelligence initiatives directly support strategic objectives.
• Translate technical capabilities and advancements into clear business outcomes that improve productivity, efficiency, and growth.
• Resolve conflicting requirements and priorities with sound technical judgment that favors long term organizational outcomes over local optimization.
• Advocate for intelligence driven solutions across the organization and influence company wide technical priorities.
• Act as a trusted technical advisor to senior engineering leadership, with IC6 scope extending to org wide and EPD level strategy.
• Provide mentorship and technical guidance to engineers and data scientists from mid level through senior, fostering continuous learning and technical excellence.
• Serve as a technical multiplier by raising the effectiveness of surrounding teams through design reviews, code reviews, architectural guidance, and pragmatic execution.
• Facilitate knowledge sharing across teams through documentation, design writeups, technical discussions, and mentorship programs.
• Act as a voice for engineers by synthesizing feedback, surfacing gaps and risks, and communicating them clearly to leadership.
• Contribute to multi year technical vision and roadmap planning, anticipating future scale, complexity, and organizational needs.
• Identify architectural, operational, and security risks early and mobilize proactive mitigation plans across org boundaries.
• Partner closely with managers, product leaders, and senior engineers to ensure ambitious initiatives remain feasible, sustainable, and well aligned.
• For IC6 scope, influence technical direction beyond CIT and partner directly with senior EPD leadership on company wide strategy.
• Lead and support critical, high impact initiatives by defining technical direction, clarifying requirements, gathering estimates, and ensuring delivery against milestones.
• Drive execution on complex projects with significant ambiguity or high cost of failure.
• Improve engineering effectiveness by championing best practices such as CI, automated testing, reliability reviews, and clear ownership models.
• Promote a bias toward action, thoughtful experimentation, and continuous learning.
• Model excellence in engineering craft, collaboration, accountability, and inclusive behavior.
• Lead by example in living Dropbox values, including integrity, ownership, simplicity, and inclusivity.
• Support hiring by interviewing, calibrating candidates against a high technical bar, and representing Dropbox authentically to candidates and partners.

Requirements

• 12+ years of professional experience in software engineering, with depth in areas such as intelligent workflows, enterprise scale AI adoption, automation, or data engineering.
• Proven track record of leading large scale, multi team technical initiatives from conception to production, including solving ambiguous problems, setting technical vision, and driving impact without direct authority.
• Strong architectural judgment and systems thinking, with the ability to balance short term delivery with long term sustainability, scalability, and operational excellence.
• Demonstrated ability to influence across teams and disciplines through technical leadership, collaboration, and sound decision making rather than formal authority.
• Experience mentoring engineers and raising the technical bar of an organization through design reviews, code reviews, and technical guidance.
• Exceptional written and verbal communication skills, with the ability to clearly explain complex technical concepts, translate technical strategy to diverse audiences, and influence stakeholders at all levels.

Role Description

The Principal Software Engineer is a highly skilled expert responsible for shaping and executing the organization’s intelligence vision. This role integrates expertise in Artificial Intelligence (AI), Machine Learning (ML), Automation, Data Analytics and Visualization to deliver transformative customer, partner, and colleague experiences that drive revenue growth and enhance productivity.

The position defines the technical direction for intelligence initiatives, leading the design, development, and deployment of robust, scalable, and secure AI solutions while fostering innovation through emerging technologies.

A critical aspect of the role is providing partnership, mentorship and technical guidance, cultivating a culture of excellence and continuous learning. Through close cross-functional collaboration across teams and stakeholders, the role ensures technical efforts are strategically aligned and deliver measurable impact. Additionally, the position plays a central role in strategic problem-solving, addressing complex challenges in intelligence systems and data pipelines, and making informed architectural decisions that ensure long-term scalability and success.

Responsibilities

• Define, drive, and communicate the technical vision for intelligence, AI, and data initiatives, ensuring alignment with CIT strategy, EPD goals, and broader organizational objectives.
• Take a holistic view of CIT systems and architecture to ensure they are scalable, reliable, secure, and maintainable over multiple years.
• Lead the design, development, and deployment of high performance AI systems, data pipelines, and intelligent services from conception through production.
• Make strategic architectural decisions to address complex AI, data, and platform challenges, balancing short term delivery with long term resilience and scalability
• Identify opportunities to simplify systems, reduce operational and security risk, and improve developer productivity.
• Contribute directly to prototyping, proof of concepts, and implementation of technical components when needed to validate strategy, de risk decisions, or accelerate progress.
• Architect, evolve, and scale AI, automation, and intelligence platforms that enable advanced analytics, personalization, search, and intelligent decision making.
• Drive innovation in intelligence models, distributed training, optimization techniques, and data engineering to maximize performance, quality, and business impact.
• Enhance search and discovery capabilities using intelligent algorithms, natural language processing, and modern data systems.
• Evaluate, select, and integrate emerging technologies in AI, ML, and automation to maintain a competitive and forward looking technical posture.
• Partner across engineering, product, design, infrastructure, and other stakeholders to ensure intelligence initiatives directly support strategic objectives.
• Translate technical capabilities and advancements into clear business outcomes that improve productivity, efficiency, and growth.
• Resolve conflicting requirements and priorities with sound technical judgment that favors long term organizational outcomes over local optimization.
• Advocate for intelligence driven solutions across the organization and influence company wide technical priorities.
• Act as a trusted technical advisor to senior engineering leadership, with IC6 scope extending to org wide and EPD level strategy.
• Provide mentorship and technical guidance to engineers and data scientists from mid level through senior, fostering continuous learning and technical excellence.
• Serve as a technical multiplier by raising the effectiveness of surrounding teams through design reviews, code reviews, architectural guidance, and pragmatic execution.
• Facilitate knowledge sharing across teams through documentation, design writeups, technical discussions, and mentorship programs.
• Act as a voice for engineers by synthesizing feedback, surfacing gaps and risks, and communicating them clearly to leadership.
• Contribute to multi year technical vision and roadmap planning, anticipating future scale, complexity, and organizational needs.
• Identify architectural, operational, and security risks early and mobilize proactive mitigation plans across org boundaries.
• Partner closely with managers, product leaders, and senior engineers to ensure ambitious initiatives remain feasible, sustainable, and well aligned.
• For IC6 scope, influence technical direction beyond CIT and partner directly with senior EPD leadership on company wide strategy.
• Lead and support critical, high impact initiatives by defining technical direction, clarifying requirements, gathering estimates, and ensuring delivery against milestones.
• Drive execution on complex projects with significant ambiguity or high cost of failure.
• Improve engineering effectiveness by championing best practices such as CI, automated testing, reliability reviews, and clear ownership models.
• Promote a bias toward action, thoughtful experimentation, and continuous learning.
• Model excellence in engineering craft, collaboration, accountability, and inclusive behavior.
• Lead by example in living Dropbox values, including integrity, ownership, simplicity, and inclusivity.
• Support hiring by interviewing, calibrating candidates against a high technical bar, and representing Dropbox authentically to candidates and partners.

Requirements

• 12+ years of professional experience in software engineering, with depth in areas such as intelligent workflows, enterprise scale AI adoption, automation, or data engineering.
• Proven track record of leading large scale, multi team technical initiatives from conception to production, including solving ambiguous problems, setting technical vision, and driving impact without direct authority.
• Strong architectural judgment and systems thinking, with the ability to balance short term delivery with long term sustainability, scalability, and operational excellence.
• Demonstrated ability to influence across teams and disciplines through technical leadership, collaboration, and sound decision making rather than formal authority.
• Experience mentoring engineers and raising the technical bar of an organization through design reviews, code reviews, and technical guidance.
• Exceptional written and verbal communication skills, with the ability to clearly explain complex technical concepts, translate technical strategy to diverse audiences, and influence stakeholders at all levels.

Your role
As an Applied Scientist at Dialpad, you'll be a key driver within our AI team, conducting R&D to power the next generation of autonomous voice agents. While traditional NLP focuses on analyzing static text, your work will center on real-time, multimodal systems that can listen, reason, and take action during live customer interactions. A major focus of the team is advancing DialpadGPT, our proprietary LLM, specifically optimizing it to drive orchestrated agentic workflows and handle complex task execution. Beyond the technical skills, we are a team that values collaboration, continuous learning, and the application of diverse perspectives to solve complex problems. Collaboration will be key as you work alongside our engineering, design, and product teams to build groundbreaking agentic applications.

If you're passionate about agentic and multimodal AI and contributing to a team that's changing the face of business communications, you'll find yourself right at home with us.

This position reports to the Senior Manager of the NLP team and has the opportunity to be based in Vancouver, BC.

What you’ll do

• Research and develop state-of-the-art algorithms for autonomous voice agents, specifically focusing on real-time speech processing and reasoning loops.
• Advance DialpadGPT: Design and execute distributed training strategies to optimize our proprietary LLMs for agentic behaviors, including precise tool use, instruction following, and latency-constrained generation.
• Conduct rigorous evaluation and monitoring of model performances and troubleshoot issues with a keen understanding of resultant business impacts.
• Design and implement orchestration layers that effectively chain LLMs with external tools and APIs to solve complex customer problems autonomously.
• Work with large-scale multimodal datasets (text, audio) to improve model robustness and alignment.
• Collaborate with engineering, product, and design teams to deploy scalable, low-latency models and algorithms in production.
• Submit papers to top-tier academic conferences (ACL, EMNLP, NeurIPS) and contribute to the team’s research culture.

Skills you’ll bring

• Master’s or PhD degree in Computer Science, Machine Learning, Computational Linguistics, or a related quantitative field.
• 2+ years of industry experience in Machine Learning/NLP for Master’s degree holders, or 1+ years for PhD holders.
• Deep understanding of LLMs: Demonstrated experience with training, fine-tuning (PEFT/LoRA), and alignment techniques (RLHF/DPO) for specific domains or tasks.
• Experience with Agentic Systems: Familiarity with building autonomous agents, including concepts like tool use, function calling, reasoning chains (CoT), and memory management.
• Strong proficiency in Python and PyTorch, with the ability to write clean, production-ready research code.
• Research Track Record: A history of publishing in top-tier conferences (ACL, EMNLP, NeurIPS, ICASSP) is highly valued.
• Multimodal Awareness: Familiarity with speech technologies (ASR, TTS) or processing real-time audio streams is a strong plus.
• Ability to bridge the gap between research and product, translating complex technical concepts into business value.
• Familiarity with version control tools like Git for collaborative projects.

This is Engineering at Lattice

At Lattice, we build software that helps people and organizations thrive. Our engineering team values maintainable systems, strong collaboration, and thoughtful product experiences.

As we expand AI-powered capabilities across our platform, security is a core part of how we design, build, and operate our product. Our Product Security team partners closely with engineering to ensure we ship features that are secure by default and resilient in production.

What You Will Do

You will work closely with product and platform engineering teams to improve the security of Lattice’s applications and services.

Product Security & Engineering Partnership

• Partner with engineers to identify, triage, and remediate security issues in product features and services
• Participate in security reviews and threat modeling for new features and systems
• Perform security-focused code reviews and help identify common vulnerabilities
• Contribute to secure-by-default patterns, libraries, and tooling in our TypeScript-based stack

Security Tooling & Operations

• Help implement and operate security tooling (SAST, DAST, dependency scanning, etc.)
• Support vulnerability management workflows, including internal findings and bug bounty reports
• Assist in investigating security issues and assessing risk and impact

Cloud & Platform Security

• Collaborate with platform and infrastructure teams to improve application and cloud security posture
• Contribute to improving security practices in AWS-based environments

AI/LLM Security

• Assist in identifying and mitigating risks in AI/LLM-powered features, including prompt injection, data leakage, and unsafe output handling
• Apply emerging best practices (OWASP Top 10 for LLM Applications) to real product use cases

Security Enablement

• • Contribute to security guidance, documentation, and training for engineering teams
  • Help improve how security is integrated into the development lifecycle

What You Will Bring to the Table

Experience that is important for you to have at some level:

• 1–3+ years of experience in product security, application security, or software engineering
• Experience writing and maintaining code in JavaScript/TypeScript (or similar languages like Python or Ruby)
• Familiarity with common web and API vulnerabilities (e.g., OWASP Top 10)
• Exposure to security testing tools (SAST, DAST, dependency scanning, etc.)
• Experience working in or with cloud environments (AWS or similar)

Technical Approach

• Ability to identify common security risks and suggest practical mitigations
• Understanding of secure coding practices and basic security controls
• Interest in how security decisions impact real-world product systems

Collaboration & Growth

• Strong communication skills and ability to work closely with engineering teams
• Willingness to ask questions, learn quickly, and take ownership of well-scoped problems
• Ability to contribute to team discussions and share security context effectively

Experience that would be nice to have:

• Experience with modern web architectures (Next.js, NestJS, GraphQL)
• Familiarity with containerization or Kubernetes
• Experience or interest in AI/LLM security, including

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 $93,750 - CAD $125,000. This position is also eligible for incentive 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 state 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.

#LI-remote

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.

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

About Us:
Trusted and loved by 25 million educators, students, and families worldwide, Seesaw is the only elementary learning experience platform, offering a suite of award-winning tools, resources, and curriculum for teachers to deliver joyful, inclusive instruction.  Through interactive lessons, digital portfolios, and two-way communication features, Seesaw keeps everyone in the learning loop by providing continuous visibility into the student's learning experience to support and celebrate their learning.

Our Mission:
Seesaw’s mission is to provide every elementary student with joyful and connected learning experiences that lay the foundation for success in life. 

Your Team:
The Product Marketing Manager at Seesaw will actively engage with our marketing and sales teams globally, fostering collaboration on strategic initiatives and playing a key role in developing comprehensive marketing plans.

The Role
We are looking for a strategic, high-impact Senior Product Marketing Manager to serve as the connective tissue between our Product, Sales, and Customer Success teams. You won't just be "launching features"; you will be the architect of our Go-To-Market (GTM) strategy as we expand Seesaw’s footprint in the US, UK, Australia, the Middle East and North Africa, and Latin America markets, or new functional areas and product categories.

This is a pivotal role for a "full-stack" marketer who thrives on ambiguity, loves deep-diving into educator personas, and can translate complex technical roadmaps into compelling narratives that drive adoption and revenue.

Your Responsibilities:

• GTM Ownership: Lead the end-to-end GTM strategy for new product functions and categories. You will define the market opportunity, naming, positioning, and pricing for Seesaw’s next generation of tools.
• Marketing Campaigns: Develop campaign messaging for our core Seesaw platform as well as curriculum products such as Early Literacy, English Language Development, I Read Arabic, I Start Arabic and more.  
• The Bridge-Builder: Act as the primary liaison between Product (to influence the roadmap based on market feedback), Sales (to provide the talk tracks and collateral needed to win), and Customer Success (to ensure long-term adoption and expansion).
• Persona & Market Intelligence: Become the resident expert on Seesaw messaging for the elementary education landscape in our core global markets. Conduct competitive analysis and user research to identify gaps in the market and opportunities for Seesaw to lead.
• Sales Enablement: Develop high-impact sales toolkits, including pitch decks, case studies, battlecards, and ROI calculators that empower our field teams to speak confidently to District Leaders and Administrators.
• Narrative Excellence: Craft clear, emotive, and benefit-driven messaging that resonates with our diverse audience of teachers, students, and families, ensuring it aligns with our mission of "joyful and connected learning."

Your Requirements:

• The Strategist: You have 5+ years of experience in Product Marketing (EdTech or SaaS experience is a major plus). You don't just execute; you think three steps ahead.
• The Communicator: You can distill complex product features into simple, "lightbulb moment" value propositions.
• The Orchestrator: You are a natural project manager who can rally cross-functional teams around a shared launch goal.
• Data-Informed: You use qualitative feedback and quantitative data to validate your hypotheses and measure the success of your GTM efforts.
• Empathetic: You have a deep appreciation for the challenges facing educators and a passion for improving the lives of elementary students.

The annual hiring base salary for this position is $100,000 - $115,000 USD
This is an Exempt position.

Benefits include: Medical/Dental + Orthodontics/Vision Coverage, 401(k) Match, Flexible Paid Time Off, Mindfulness First Fridays, Monthly Technology Stipend, Home Office Setup Stipend, Professional Development Stipend, Paid Parental Leave, Charitable Donation Matching, Volunteer Days.

Seesaw cares about building a diverse and inclusive team to better advocate for the needs of our incredibly diverse K-12 users.

We prioritize work-life balance and actually walk the walk — we care a lot about our work, but care more about our employee's well-being. We encourage everyone to work at a sustainable pace and have a flexible vacation policy that people actually use.

Seesaw provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, religious creed, color, sex, sex stereotype, gender, gender identity/gender expression/transgender, national origin, ancestry, physical or mental disability, medical condition, genetic information/characteristics, marital status/registered domestic partner status, age, sexual orientation, or military or veteran status. In addition to federal law requirements, Seesaw complies with applicable state and local laws governing nondiscrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Seesaw is committed to protecting your personal data. Learn more about the personal information we collect, how we use it, and how to exercise your rights here: U.S. Privacy Notice.

What You'll Be Doing:

• Work directly on building, deploying, and iterating on machine learning models and agentic workflow features that address real customer needs
• Apply ML techniques to improve accuracy and overall system performance, ensuring solutions are robust, reliable, and production-ready for customers
• Improve, implement, and validate ML models and agentic workflows supporting submission intake, underwriting decision-making, and automation tasks
• Deploy and adapt autonomous agent behaviors into customer-specific workflows, translating core AI capabilities into practical solutions
• Develop and maintain evaluation pipelines, monitoring systems, and performance metrics to ensure reliability under evolving production conditions
• Monitor production systems via logs, metrics, and user feedback to diagnose issues, debug failures, and drive resolution
• Take end-to-end ownership of problems — implementing fixes or coordinating with engineering and infrastructure teams as needed
• Partner closely with Data Science and Engineering teams to iterate quickly and deliver high-impact solutions

Who We Hope You Are:

• Bachelor's or master’s degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or a related field with foundational knowledge in machine learning, deep learning, and natural language processing.
• Experience working in a fast-paced, cross-functional environment
• 2+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role delivering ML solutions in production
• Experience working directly with customers or stakeholders to translate business needs into technical solutions
• Hands-on experience adapting, extending, and deploying ML/LLM systems (including agentic workflows and prompt engineering) in real-world use cases
• Strong experience with experimentation, evaluation, and monitoring pipelines, including analyzing production logs and debugging systems
• Experience deploying and iterating on ML systems in cloud environments in collaboration with engineering teams
• Proven track record of ownership — driving issues through to resolution in production systems

Base Salary Range: $155,000 - $180,000
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package also includes bonus, stock options, benefits and additional perks. 

The Interview Overview:

Below you'll find an outline of the interview plan for our Staff AI Developer position. Please note that this is what we expect the process to look like; we may ask you for supplemental information or require an additional step before making a final decision.

1. 30 min - Phone call with a member of our Talent Team
2. 75 min - Zoom interview with the Hiring Manager
3. Skills Evaluation - Take-home Assignment
4. 75 hr - Technical Interview with Team
5. 30 min - Executive Interview

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

Product Director, Common Voice (12 month Fixed-Term)

Mozilla Foundation is a non-profit building a better technology future — powered by people, open by design, fueled by imagination.

We deliver people-first alternatives to today’s extractive systems. We build side by side with developers, innovators and advocates, united in the belief that a better technology future is not only possible — it’s ours to create.

Team

The Tech Platforms team stewards and evolves shared technology platforms that power Mozilla Foundation programs and enable effective, secure, and scalable ways of working. Within the Tech Platforms team, Mozilla Common Voice is the flagship intervention to mitigate bias within AI - in particular by making it possible for speakers of the world’s 7000+ languages, and traditionally marginalized demographic communities, to be represented in AI training sets, and meaningfully engaged in building AI.

Mozilla Common Voice is a data crowdsourcing platform that supports 300+ communities around the world, and to which more than half a million people have contributed. The dataset is used by these communities, and also in technology and research organizations all over the world.

The Common Voice work spans product development, platform engineering, data stewardship, privacy and compliance, and community engagement. The team collaborates closely with contributors, researchers, and partners across regions and languages to ensure the platform remains trustworthy, inclusive, and sustainable while supporting long-term impact and future growth.

The Product Director, Common Voice is responsible for the overall success of the Common Voice project. This role is primarily accountable for product vision, roadmap, prioritization, and long-term direction, while also taking on interim community management responsibilities and providing engineering leadership and delivery oversight.

Job responsibilities

Here are some projects you'll likely work on in your first 6 months:

• Deliver the 2026 maintenance+ roadmap, ensuring platform stability, reliability, security, and progress on critical technical debt.
• Define and track success metrics aligned to 2026 goals and Tech Platforms objectives.
• Lead development of a proposed 2027+ product roadmap, including growth scenarios, resourcing implications, and strategic tradeoffs.
• Support the Common Voice project in funding proposals and partnership discussions as needed.
• Take on interim community manager responsibilities while the Common Voice team is re-scoped and shaped.
• Ensure continuity, trust, and responsiveness for the Mozilla Common Voice community during the transition period.
• Oversee community communications, contributor engagement, and language onboarding processes within resourcing constraints.
• Set clear goals, priorities, and expectations for engineering contributors in alignment with product objectives.
• Ensure effective collaboration between engineering, data, privacy, and infrastructure partners.

As a  Product Director, Common Voice at Mozilla, you will work on…

Product Ownership & Strategic Leadership - 50% of time

• Serve as the accountable product owner for Common Voice, with responsibility for product vision, roadmap, and prioritization
• Deliver the 2026 maintenance+ roadmap, ensuring platform stability, reliability, security, and progress on critical technical debt
• Define and track success metrics aligned to 2026 goals and Tech Platforms objectives
• Lead development of a proposed 2027+ product roadmap, including growth scenarios, resourcing implications, and strategic tradeoffs
• Represent Common Voice project in funding proposals and partnership discussions as needed. 

Community Management & Stewardship (Interim) — 30% of time

• Take on interim community manager responsibilities while the Common Voice team is re-scoped and shaped
• Ensure continuity, trust, and responsiveness for the Mozilla Common Voice community during the transition period
• Oversee community communications, contributor engagement, and language onboarding processes within resourcing constraints
• Balance community needs with platform realities and clearly communicate priorities and limitations

Engineering Management & Delivery leadership - 20% of time

• Provide direct people management and delivery leadership for Common Voice engineering staff and contractors
• Set clear goals, priorities, and expectations for engineering contributors in alignment with product objectives
• Ensure effective collaboration between engineering, data, privacy, and infrastructure partners

Your Professional Profile:

• 5+ years of progressively senior Product Management experience, ideally within a small, agile team.
• Strong product judgment and experience setting direction, prioritizing work, and managing tradeoffs in a complex environment.
• Knowledge of linguistics or languages, with multilinguality a plus.
• At least a basic grounding in computational linguistics or NLP.
• Fantastic communication skills are required - the team and community are global and distributed. You will be required to communicate with internal and external collaborators, all of whom have very different perspectives, backgrounds and contexts.
• Excellent judgment, and proven in triaging a lot of inbound signals and needs.
• Self motivated and driven - a proactive problem solver - this is a small team.
• Strong affinity for research and metrics - ideally experience delivering user research plans and interfacing directly with communities, users and collaborators.
• Experience working directly and closely with linguists, language activists, software engineers, data scientists and designers.

We Are Excited To See Any Additional Experience With:

• Some experience in Machine Learning-driven projects, or some academic training in ML/AI.
• Knowledge of Voice / Speech AI.

Salary and Benefits Information:

Mozilla Foundation is dedicated to fair and equitable compensation for our staff. We aim to pay a competitive and market-based salary based on the responsibilities and requirements of the role. We do not ask for, or take into account, salary histories in our offer process.

The starting salary ranges for this role are listed below. These four countries are where we most commonly employ staff.

• Germany: €101,347.20 — €113,888.92
• UK: £83,980.80 — £94,373.42
• Canada: $174,960.00 — $196,611.30
• US: $129,600.00 — $145,638.00

Some regions fall into a higher salary market and this is reflected in the example ranges below: 

• London: £104,976.00 — £117,966.78
• New York City: $162,000.00 — $182,047.50
• Maryland/DC: $155,520.00 — $174,765.60

The range for your specific location will be discussed in screening conversations if your application is successful.

We offer the following benefits:

• Private Medical Insurance
• Extended Sick Leave
• Global Employee Assistance Program (EAP)
• Retirement Plan contributions
• Paid Time Off: 20 days annual leave + sick days and your birthday  
• Company Holidays + Shutdown
• Wellness budget
• Professional Development budget
• Top up program for Pregnancy and Parental leaves

Benefits are subject to change at any time at the discretion of Mozilla Foundation.

Mozilla Foundation Hiring Practices:

Mozilla understands that valuing diverse creative practices and forms of knowledge are crucial to and enrich the company’s core mission. We encourage applications from everyone, including members of all equity-seeking communities, such as (but certainly not limited to) women, racialized and Indigenous persons, persons with disabilities, and persons of all sexual orientations and gender identities and expressions.

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

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 accommodation at accommodation@mozillafoundation.org.

#LI-REMOTE 

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role: 

We are seeking a Staff Software Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers.

This role owns the self-sourcing and extraction foundation used by multiple teams across the organization. Today, human validation is used as a safety net. Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability.

You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems.

Who You Are:

• 10+ years of experience building and operating large-scale production systems
• Proven experience designing data ingestion, extraction, or processing systems at scale
• Deep expertise in one or more of:
  • Distributed systems
  • Data platforms and pipelines
  • AI/ML-powered extraction or classification systems
  • Platform or infrastructure engineering
• Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
• Strong understanding of system reliability, observability, failure modes, and iterative hardening
• Experience reducing operational or human overhead through better system design
• Track record of technical leadership across teams without formal people management
• Comfortable operating in ambiguity and driving clarity where none exists
• Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems

Nice to Have

• Experience with document understanding, NLP, or financial data extraction
• Experience building provenance, lineage, or confidence-scoring systems
• Familiarity with cloud-native architectures and modern data stacks
• Experience shaping or owning internal platforms used by multiple teams

What You’ll Do: 

• Own the architecture and evolution of our large-scale data extraction and normalization platform
• Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability
• Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards
• Establish clear system contracts for correctness, traceability, and confidence (e.g., “where did this number come from?”)
• Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity
• Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary
• Partner with product and downstream consumers to define quality bars, SLAs, and success metrics
• Serve as a technical escalation point for production issues, reliability failures, and systemic risks
• Mentor senior engineers, shape technical culture, and raise expectations for system design and execution
• Contribute to long-term technical strategy while remaining hands-on with critical implementations

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role: 

We are seeking a Principal Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers.

This role owns the self-sourcing and extraction foundation used by multiple teams across the organization. Today, human validation is used as a safety net. Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability.

You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems.

Who You Are:

• 15+ years of experience building and operating large-scale production systems
• Proven experience designing data ingestion, extraction, or processing systems at scale
• Deep expertise in one or more of:
  • Distributed systems
  • Data platforms and pipelines
  • AI/ML-powered extraction or classification systems
  • Platform or infrastructure engineering
• Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
• Strong understanding of system reliability, observability, failure modes, and iterative hardening
• Experience reducing operational or human overhead through better system design
• Track record of technical leadership across teams without formal people management
• Comfortable operating in ambiguity and driving clarity where none exists
• Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems
• Nice to Have
  • Experience with document understanding, NLP, or financial data extraction
  • Experience building provenance, lineage, or confidence-scoring systems
  • Familiarity with cloud-native architectures and modern data stacks
  • Experience shaping or owning internal platforms used by multiple teams

What You’ll Do: 

• Own the architecture and evolution of our large-scale data extraction and normalization platform
• Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability
• Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards
• Establish clear system contracts for correctness, traceability, and confidence (e.g., “where did this number come from?”)
• Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity
• Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary
• Partner with product and downstream consumers to define quality bars, SLAs, and success metrics
• Serve as a technical escalation point for production issues, reliability failures, and systemic risks
• Mentor senior engineers, shape technical culture, and raise expectations for system design and execution
• Contribute to long-term technical strategy while remaining hands-on with critical implementations

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

POSITION DESCRIPTION  

ROLE: RECRUITER  
TEAM: TALENT  
LOCATION: TORONTO (HYBRID)  

COMPANY OVERVIEW  

Salt is a North American marketing agency that creates connected experiences through creative, digital & media innovation. 

Our mission is to “Earn the World’s Attention” and Salt is built to find, develop, execute, and amplify the ideas that are worthy of our clients’ audiences. We’ve structured our agency to do what’s right for our clients – to connect different perspectives, to work across mediums, and to focus on delivering meaningful, effective results. 

We’re committed to living up to the values in our name. “Salt of The Earth” means we value collaborative, humble, hard-working people here. We’re looking for people who are as smart as they are kind because we believe the right talent and the right culture help us do what’s right for our clients.   
 
ROLE OVERVIEW  
The Recruiter will partner with the Director of Talent to lead full-cycle hiring for Salt XC. From Creatives and Community Managers to Media, Design, and Digital roles, you’ll help source and secure the talent that drives our work forward.  

You’ll be hands-on in every part of the process: finding top candidates, building strong pipelines, and elevating how we show up in the market. You’re a natural relationship builder with a sharp eye for talent and a drive to make things better. You think fast, act with purpose, and bring fresh ideas to every search.  

CORE RESPONSIBILITIES  

Talent Acquisition and Sourcing 

• Run full-cycle recruitment for assigned departments, from intake to offer.
• Build proactive pipelines through research, outreach, referrals, communities, and events.
• Write inclusive, compelling job postings and calibrate success profiles with hiring managers. 

Candidate Experience and Employer Brand 

• Maintain timely, transparent communication with all candidates. 
• Prepare teams for structured, competency-based interviews and close the loop with clear feedback. 
• Support employer brand efforts through events, content, and partnerships that showcase Salt. 

Recruitment Analytics and Optimization 

• Maintain accurate ATS data; keep stages, notes, and statuses current. 
• Track and share funnel metrics such as time-to-fill, source effectiveness, and conversion. 
• Surface insights to improve speed, quality of hire, and process efficiency. 

Strategic Partnership and Stakeholder Influence 

• Consult with hiring managers on role scope, JD language, interview plans, and assessment. 
• Align searches to headcount plans and hiring priorities; set expectations on pace and pipeline health. 
• Communicate progress, risks, and recommendations clearly and proactively. 

Early Talent and Engagement Programs 

• Own outreach and logistics for intern and early-career programs in partnership with People & Culture. 
• Support campus and community engagement; track conversion and retention outcomes. 
• Provide feedback to improve programming, onboarding, and development pathway 

EXPERIENCE & SKILLS   

• 3–5 years recruiting experience, ideally in a creative or integrated agency environment. 
• Full-cycle recruiting proficiency across diverse roles (Creative, Digital, Media, Operations) with evidence of quality hires and manager satisfaction. 
• Sourcing depth using LinkedIn Recruiter, Boolean search, referrals, communities, and events; comfort building proactive pipelines. 
• ATS fluency with disciplined data hygiene and reporting; able to translate funnel data into actionable insights. 
• Stakeholder partnership skills: consultative intake, expectation setting, structured interview planning, and offer negotiation. 
• Candidate experience excellence: clear, timely communication; respectful feedback; advocacy for inclusion. 
• Process rigor: organized, detail-oriented, and consistent in documentation, compliance, and handoffs to onboarding. 
• Communication and influence: strong writing and presentation; able to advise with empathy and objectivity. 
• EDI mindset: curiosity, fairness, and commitment to broadening access and representation. 

PERKS & BENEFITS THAT SET US APART  
We don’t just talk about balance, growth, and culture, we build for it:  

• Work-Life Flexibility: Hybrid setup, up to 28 paid days off & winter holiday shutdowns.
• Comprehensive Coverage: Health, dental, and vision plans, plus Salt Bucks to spend on what matters to you—wellness, RRSPs, or extra time off.  
• Growth-Driven Culture: Dedicated Salt Days, top-tier learning access, and formal leadership development.  
• Celebration-First Mentality: Legendary team trips, seasonal socials, and Salt Swag that reps your squad.  
• Real Rewards: Referral and new business bonuses, exclusive lifestyle perks, and personalized wellness options.  
• Culture of Belonging: DEI programs, active ERGs, and a workplace where every voice counts.  

WHAT WE STAND FOR  

• Salt of the Earth: We lead with humility, honesty, and heart—always.  
• Do What’s Right: No shortcuts. We choose integrity over ease, every time.  
• Earn Your Salt: We roll up our sleeves, chase results, and celebrate the journey.  
• Make Things Better: We’re solution-seekers, always pushing for smarter ways forward.  
• Seek Different Perspectives: Diversity fuels our thinking. Inclusion drives our impact.  

The anticipated annual base salary range for this position is $65,000–$90,000. Individual compensation within this range is determined based on job-related factors such as experience, skills, level of responsibility, internal equity, and business needs. This range represents the expected base salary for this role and does not include other elements of SALT XC’s total rewards program.

About Acquia

Acquia empowers the world’s most ambitious brands to create digital customer experiences that matter. With open source Drupal at its core, the Acquia Digital Experience Platform (DXP) enables marketers, developers, and IT operations teams at thousands of global organizations to rapidly compose and deploy digital products and services that engage customers, enhance conversions, and help businesses stand out.

Headquartered in the U.S., Acquia has been named a top software company by The Software Report, rated a leader by the analyst community, and named a top place to work by the Boston Globe and the Boston Business Journal. We are Acquia. We are building for the future and we want you to be a part of it!

The Role: Acquia is seeking a Staff AI Engineer to join our AI Platform Engineering team. This is first and foremost a hands-on engineering role — you will spend the majority of your time designing, building, and shipping production-grade agentic AI workflows across the Acquia DXP. LangGraph and LangFuse are your primary tools; enterprise reliability, observability, and scale are your standards. You'll also play a light but meaningful mentoring role, helping to lift the AI engineering capability of those around you as the team grows.

Key Responsibilities

• Write and ship production AI code daily — you are an active contributor, not just an architect. 
• Architect agentic AI workflows using LangGraph — stateful, multi-agent workflows built for enterprise scale and reliability.
•  Own AI observability via LangFuse: tracing, prompt versioning, evaluation, and performance benchmarking across all model interactions.
•  Set AI engineering standards for agent design patterns, RAG, prompt management, context optimization, and tool-calling strategies.
•  Partner with product and platform teams to deliver AI architectures that meet enterprise SLA, security, and compliance requirements.
• Evaluate and adopt emerging tooling— benchmarking LLM providers, orchestration frameworks, and agentic stack improvements.
• Mentor engineers as a natural extension of your work — sharing knowledge through code reviews, pairing sessions, and design discussions, not through management overhead.
• Represent Acquia's AI capabilities in customer architectural reviews, technical discovery, and roadmap conversations.

Required Experience

• 8+ years of software engineering with 3+ years in production AI/ML or LLM systems.
• Hands-on LangGraph expertise — stateful, cyclic, multi-agent workflows at enterprise scale.
• Hands-on LangFuse expertise - tracing, evaluation, prompt management, and dataset- driven testing
• Proficiency with agent harness frameworks such as LangChain or similar (e.g. LlamaIndex, CrewAI) — composing chains, tools, memory, and retrieval pipelines.
• Deep Python proficiency and strong engineering fundamentals (testing, CI/CD, architecture).
• Cloud AI deployment experience (AWS, Azure, or GCP) including containerization and inference cost management.
• RAG architecture knowledge— vector databases, embedding models, and retrieval strategies.
• B.S. in Computer Science or equivalent practical experience.

Desired Skills

• Enterprise SaaS or CMS,  including familiarity with Acquia's Drupal-based DXP experience
• Agentic development workflow fluency  — AI-assisted coding tools (Copilot, Cursor, Claude) as everyday accelerators.
• Familiarity with persistent agent runtimes - such as OpenClaw and Hermes Agent, understanding cross-session memory, autonomous skill creation, and always-on agent infrastructure as it matures in enterprise contexts.
• LLM fine-tuning or model evaluation experience and awareness of foundational model tradeoffs.
• Human-in-the-loop — interrupt-driven agents and enterprise design
• Strong communication skills — able to present AI system design to both engineers and C-suite stakeholders.
• Senior IC track record — known for the quality of your own code and system designs, with mentoring that happens organically through great work, not through meetings.

Acquia is proud to provide best-in-class benefits offerings to our employees and their families in maintaining both a healthy body and a healthy mind. Core Benefits include: competitive healthcare coverage, wellness programs, take it when you need it time off, parental leave, recognition programs, and much more! 

Acquia is an equal opportunity (EEO) employer. We hire without regard to age, color, disability, gender (including gender identity), marital status, national origin, race, religion, sex, sexual orientation, veteran status, or any other status protected by applicable law. For more information about our commitment to inclusivity and diversity, please visit our Diversity and Inclusion page.

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role: 

We are seeking a Principal Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers.

This role owns the self-sourcing and extraction foundation used by multiple teams across the organization. Today, human validation is used as a safety net. Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability.

You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems.

Who You Are:

• 15+ years of experience building and operating large-scale production systems
• Proven experience designing data ingestion, extraction, or processing systems at scale
• Deep expertise in one or more of:
  • Distributed systems
  • Data platforms and pipelines
  • AI/ML-powered extraction or classification systems
  • Platform or infrastructure engineering
• Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
• Strong understanding of system reliability, observability, failure modes, and iterative hardening
• Experience reducing operational or human overhead through better system design
• Track record of technical leadership across teams without formal people management
• Comfortable operating in ambiguity and driving clarity where none exists
• Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems
• Nice to Have
  • Experience with document understanding, NLP, or financial data extraction
  • Experience building provenance, lineage, or confidence-scoring systems
  • Familiarity with cloud-native architectures and modern data stacks
  • Experience shaping or owning internal platforms used by multiple teams

What You’ll Do: 

• Own the architecture and evolution of our large-scale data extraction and normalization platform
• Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability
• Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards
• Establish clear system contracts for correctness, traceability, and confidence (e.g., “where did this number come from?”)
• Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity
• Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary
• Partner with product and downstream consumers to define quality bars, SLAs, and success metrics
• Serve as a technical escalation point for production issues, reliability failures, and systemic risks
• Mentor senior engineers, shape technical culture, and raise expectations for system design and execution
• Contribute to long-term technical strategy while remaining hands-on with critical implementations

About the Team:

Our diverse Product & Engineering team values innovation, collaboration, and the continuous improvement of our platform. We offer a dynamic work environment where employees can grow and thrive while working on cutting-edge technology that shapes the future of AI and search.

At AlphaSense, we believe that diverse experiences and perspectives are critical to our success. We are committed to creating an inclusive workplace where all employees feel valued and empowered to be their authentic selves.

About the Role: 

We are seeking a Staff Software Engineer to lead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system ingests filings across formats (HTML, PDF, APIs, spreadsheets), extracts and standardizes financial data using a combination of AI and deterministic systems, and delivers trusted, traceable outputs at scale to downstream financial services teams and customers.

This role owns the self-sourcing and extraction foundation used by multiple teams across the organization. Today, human validation is used as a safety net. Your mission is to systematically reduce human dependency by increasing system correctness, confidence, and trust, without sacrificing speed or scalability.

You will operate at the intersection of distributed systems, AI-driven extraction, data quality, and platform architecture, raising the technical bar and reshaping how we build reliable systems.

Who You Are:

• 10+ years of experience building and operating large-scale production systems
• Proven experience designing data ingestion, extraction, or processing systems at scale
• Deep expertise in one or more of:
  • Distributed systems
  • Data platforms and pipelines
  • AI/ML-powered extraction or classification systems
  • Platform or infrastructure engineering
• Demonstrated ability to design trustworthy systems that combine probabilistic (AI) and deterministic approaches
• Strong understanding of system reliability, observability, failure modes, and iterative hardening
• Experience reducing operational or human overhead through better system design
• Track record of technical leadership across teams without formal people management
• Comfortable operating in ambiguity and driving clarity where none exists
• Passion for using AI responsibly and effectively to deliver scalable, high-confidence systems

Nice to Have

• • Experience with document understanding, NLP, or financial data extraction
  • Experience building provenance, lineage, or confidence-scoring systems
  • Familiarity with cloud-native architectures and modern data stacks
  • Experience shaping or owning internal platforms used by multiple teams

What You’ll Do: 

• Own the architecture and evolution of our large-scale data extraction and normalization platform
• Design systems that process hundreds of thousands of records across heterogeneous sources (PDF, HTML, APIs, XLS) with high reliability
• Define and implement strategies to minimize human-in-the-loop validation through AI-based validation, confidence scoring, provenance tracking, and deterministic safeguards
• Establish clear system contracts for correctness, traceability, and confidence (e.g., “where did this number come from?”)
• Balance AI-driven approaches with procedural and rules-based systems where they improve reliability and explainabilityIdentify and remediate architectural and operational bottlenecks impacting scale, accuracy, and developer velocity
• Act as the technical authority to block poor designs, redesign critical systems, and introduce new platforms or tooling when necessary
• Partner with product and downstream consumers to define quality bars, SLAs, and success metrics
• Serve as a technical escalation point for production issues, reliability failures, and systemic risks
• Mentor senior engineers, shape technical culture, and raise expectations for system design and execution
• Contribute to long-term technical strategy while remaining hands-on with critical implementations

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

What we’re looking for

The Machine Learning Platform team (MLP) is seeking a Senior Software Engineer II to design and implement the secure, highly scalable, and high-performance pipelines that govern the end-to-end lifecycle of ML models.

You will work at the intersection of Data Science and DevOps, building the "connective tissue" that empowers our product portfolio to leverage technologies like Generative AI, Natural Language Processing (NLP), and real-time classification. We are looking for a subject matter expert who will drive innovation and deliver results that meet the dynamic needs of a high-growth AI environment. You will report to the Senior Engineering Manager on the MLP Solutions team.

What you’ll be working on

• Build and maintain robust ML systems using Python (Pandas/NumPy, PyTorch/transformers) to support efficient ML operations.
• Design ML cloud infrastructure using AWS services, ensuring the platform is built for reuse, scalability, and high-volume throughput.
• Collaborate with application engineers to integrate, test, and monitor ML model services across SurveyMonkey’s microservices architecture.
• Act as a consultant to internal feature teams, educating and influencing decisions regarding ML tooling and infrastructure.
• Incorporate telemetry into the platform for complex failure mode analysis, ensuring real-time reliability for millions of daily survey responses.
• Serve as a technical leader and mentor, championing high standards in coding, documentation, and architectural best practices to foster the professional growth of junior engineers on the MLP team.

We’d love to hear from people with

• 8+ years of professional ML development experience with a proven track record of designing and implementing ML infrastructure in AWS.
• Mastery of ML concepts (supervised/unsupervised learning) and deep understanding of Large Language Models (LLMs) and NLP.
• Expert-level Python skills and experience with high-scale data processing (PySpark, etc.).
• Comfortable with Unix/Linux systems and experienced in deploying end-to-end solutions for real-time applications (spam detection, personalization, ranking).
• Bachelor’s Degree in Computer Science, Data Science, Software Engineering, Mathematics, Statistics, or a related quantitative field.

The base pay provided for this position ranges from CAD $126,400.00/ year - $158,000.00/ 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

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

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

About the role:

Responsibilities:

• Design, develop, and deploy Cresta’s AI Agent solutions and proprietary models.
• Focus on practical AI challenges such as improving reasoning, planning capabilities, and evaluation in real-world scenarios.
• Collaborate with cross-functional teams including front-end and back-end software engineers to integrate AI Agents into Cresta’s customer solutions.
• Lead initiatives to scale AI systems for production environments, ensuring performance and reliability across use cases.
• Contribute to solving cutting-edge problems in AI and help define the future roadmap for Cresta’s AI Agents.
• Innovate and research ways to improve security, cost-efficiency, and reliability of AI systems.

Qualifications We Value:

Responsibilities:

• Assist with all stages of our AI Delivery projects - designing, building, deploying, and tuning AI solutions for multiple customers.
• Collaborate with internal and external stakeholders to design and build solutions that help customers achieve their business objectives using Cresta's AI product suite.
• Assist in designing solutions for contact centers in sales, retention, collections, and customer service across a range of verticals, from financial services to telecommunications and everything in between.
• Define labeling guidelines to be used to train conversational AI models, and assist with labeling as needed.
• Lead model maintenance efforts to ensure that Cresta's AI models continue to meet our quality standards.
• Design and develop virtual agent solutions using Google's Dialogflow CX.

Qualifications We Value:

Cresta is on a mission to turn every customer conversation into a competitive advantage by unlocking the true potential of the contact center. Our platform combines the best of AI and human intelligence to help contact centers discover customer insights and behavioral best practices, automate conversations and inefficient processes, and empower every team member to work smarter and faster. Born from the prestigious Stanford AI lab, Cresta's co-founder and chairman is Sebastian Thrun, the genius behind Google X, Waymo, Udacity, and more. Our leadership also includes CEO, Ping Wu, the co-founder of Google Contact Center AI and Vertex AI platform, and co-founder, Tim Shi, an early member of Open AI.

Join us on this thrilling journey to revolutionize the workforce with AI. The future of work is here, and it's at Cresta.

About the role:

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include:

• Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.
• Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.
• Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities:

• Lead the design and development of Cresta’s next-generation AI Agents and Agentic Assist systems, defining system architecture and core modeling approaches.
• Architect intelligent, multi-step agent workflows that combine real-time guidance, knowledge retrieval, reasoning, summarization, and automated actions into cohesive production systems.
• Design, deploy, and optimize LLM-powered systems, including Retrieval-Augmented Generation (RAG) pipelines, multi-agent orchestration, and domain-adapted models.
• Improve reasoning, planning, and tool-use capabilities in real-world AI applications.
• Develop evaluation strategies for complex, non-deterministic systems, including offline benchmarking, online experimentation, and LLM-as-a-judge methodologies.
• Diagnose and mitigate real-world failure modes such as hallucinations, retrieval errors, tool misuse, prompt brittleness, and multi-step reasoning breakdowns.
• Define and measure quality metrics (e.g., accuracy, faithfulness, task completion, latency, cost, robustness) to improve system reliability and performance.
• Optimize AI systems for scalability, latency, security, and cost efficiency in production environments.
• Collaborate cross-functionally with product, frontend, and backend teams to integrate AI capabilities seamlessly into Cresta’s platform.
• Mentor engineers, contribute to technical strategy, and help shape the roadmap for Cresta’s AI systems.

Qualifications We Value:

• Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or Ph.D. preferred.
• 5–8+ years of industry experience building and deploying machine learning systems in production, including significant experience working with LLMs.
• Strong expertise in NLP, Generative AI, transformer architectures, embeddings, and retrieval systems.
• Proven experience designing and deploying Retrieval-Augmented Generation (RAG) systems in enterprise environments.
• Experience building and evaluating complex agentic or multi-step LLM workflows.
• Strong knowledge of modern ML frameworks and tools (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
• Demonstrated ability to optimize real-time ML systems for performance, scalability, and reliability.
• Strong technical leadership skills, with the ability to influence cross-functional decisions and raise the engineering bar.

Perks & Benefits:

• We offer Cresta employees a variety of medical, dental, and vision plans, designed to fit you and your family’s needs
• Paid parental leave to support you and your family
• Monthly Health & Wellness allowance
• Work from home office stipend to help you succeed in a remote environment
• Lunch reimbursement for in-office employees 
• PTO: 3 weeks in Canada 

Compensation for this position includes a base salary, equity, and a variety of benefits. Actual base salaries will be based on candidate-specific factors, including experience, skillset, and location, and local minimum pay requirements as applicable. We are actively hiring for this role in the US and Canada. Your recruiter can provide further details.

This posting will be used to fill a newly-created role.

We have noticed a rise in recruiting impersonations across the industry, where scammers attempt to access candidates' personal and financial information through fake interviews and offers. All Cresta recruiting email communications will always come from the @cresta.ai domain. Any outreach claiming to be from Cresta via other sources should be ignored.  If you are uncertain whether you have been contacted by an official Cresta employee, reach out to recruiting@cresta.ai

Overview

We are seeking a hands-on Director of AI Software Engineering to lead and scale AI engineering efforts supporting multiple business units across Governance, Risk, and Compliance (GRC). This role sits at the intersection of product delivery, platform evolution, and applied AI—driving real-world impact across core workflows.

This is not a pure management role. We are looking for a builder who leads from the front, someone who has recently written production code, shipped systems end-to-end, and can operate comfortably in ambiguity while aligning teams and stakeholders.

What You’ll Do

Lead AI Engineering Across GRC

Own delivery of AI-powered capabilities embedded directly into business unit workflows (e.g., risk analysis, compliance automation, reporting, due diligence)
Partner with product, data, and platform teams to translate business problems into scalable AI systems

Stay Hands-On

• Contribute to architecture, code reviews, and critical path implementation
• Prototype and validate new approaches (LLMs, agents, retrieval systems, classification pipelines, etc.)
• Set engineering standards for performance, reliability, and cost efficiency

Build and Scale Teams

• Lead and mentor a high-performing team of AI/ML and software engineers
• Drive hiring, coaching, and career development
• Establish a culture of ownership, speed, and technical excellence

Drive Execution

• Deliver production-grade systems—not experiments
• Balance speed with rigor (security, privacy, compliance)
• Operate across multiple concurrent initiatives with clear prioritization

Communicate and Influence

• Act as a bridge between engineering and business stakeholders
• Clearly articulate trade-offs, risks, and outcomes to senior leadership
• Align cross-functional teams around shared goals and timelines

What We’re Looking For

Proven Builder

• 10+ years in software engineering, with recent hands-on coding experience
• Demonstrated track record of shipping production systems at scale
• Experience with modern AI/ML systems (LLMs, NLP, search, or data platforms)

Technical Depth

• Strong backend engineering skills (e.g., Python, Java, or similar)
• Experience with distributed systems, APIs, and cloud platforms (AWS/GCP/Azure)
• Familiarity with modern AI stacks (e.g., vector search, embeddings, model serving, agent frameworks)

Leadership with Credibility

• Experience leading engineering teams while remaining technically engaged
• Ability to earn trust with senior engineers and challenge them constructively

Strong Communicator

• Can simplify complex technical concepts for non-technical stakeholders
• Comfortable operating at both executive and implementation levels

Execution-Oriented

• Bias for action; thrives in fast-moving, ambiguous environments
• Focused on delivering measurable business impact—not just technical output

Nice to Have

• Experience in GRC, fintech, or regulated environments
• Exposure to FedRAMP or similar compliance frameworks
• Background in building AI-powered products (not just research)

Why This Role

• Direct influence on how AI transforms core GRC workflows
• Opportunity to define and scale AI-native systems across the platform
• High visibility with senior leadership and business stakeholders
• Build real products used by customers, not internal experiments

Location: Remote (USA & Canada only — PST hours preferred) with some office travel required
Annual salary: USD 125,000 - USD 175,000
Type: Full Time
Reports to: Director of Product Design

The Role

We are looking for a talented and motivated Product Designer to own the design and user experience (UX) of Playground. This role will be critical in creating an engaging, family-friendly interface that enhances how users interact with Playground. You will collaborate closely with our product and engineering teams to design and iterate on experiences that support our mission to connect families through fun and physical activity. Using first principles thinking, you’ll be tirelessly seeking opportunities to improve the first-time user experience, the core browsing experience, and other features intended to engage and retain users.

Key Responsibilities

• Lead the design process for the OS, focusing on user needs, usability, and delightful interactions for both kids and adults.
• Design and prototype the UI/UX for our custom Android-based operating system, including navigation, settings, and play modes.
• Design user-friendly web-based features that allow users to manage their Playground account off-device
• Work closely with product leaders, engineers, and marketers to understand requirements, align on objectives, and deliver innovative design solutions.
• Create wireframes, prototypes, and high-fidelity designs for new features. Collaborate with engineering to refine designs based on feedback and testing.
• Work to build more consistent practice around team-wide customer empathy by participating in and leading research and testing
• Conduct user research and usability testing to validate design decisions, identify pain points, and iterate on solutions.
• Help build and maintain a consistent design language and design system for both the OS and web platforms.
• Conduct regular audits and usability testing to ensure the design system meets user needs and maintains a high level of quality.
• Advocate for the value and importance of a design system to stakeholders across the company.

Qualifications 

• Bachelor’s or Master’s degree in Design, Human-Computer Interaction, or a related field.
• 8+ years of experience in product design, UI/UX design, or a similar role.
• Experience with software development and the processes and practices associated with it.
• Strong portfolio demonstrating experience in interaction design, visual design, and user experience, with a focus on consumer-facing digital products.
• An eye for high-quality, well-crafted visual and interaction design.
• Proficiency with design and prototyping tools such as Figma, Sketch or similar.
• Strong leadership and communication skills, with the ability to articulate design decisions and advocate for user-centered design.
• Ability to balance multiple projects and priorities in a fast-paced, dynamic environment.
• A knack for figuring out ambiguous problems and shaping them into clear goals.
• Passion for creating engaging experiences for families, children, and friends.

Nice To Have

• Experience designing operating systems, or 10-foot UI experiences.
• Experience conducting user research and usability testing.
• Familiarity with designing for entertainment experiences with a library of content that is curated and editorialized.
• Knowledge of design systems and creating reusable design components.

Position Summary

League is seeking a Senior ML Engineer to join our AI Models team, focused on advancing innovation in small language models (SLMs) and applied AI systems.

This role sits at the intersection of research and engineering, with a strong emphasis on experimentation, model development, and applied system design. You will work closely with AI leadership to explore, prototype, and operationalize new approaches to domain-specific language models that power League’s healthcare platform.

Unlike a traditional engineering role, this position is R&D-focused, designed for someone who can:

• Translate emerging research into practical implementations
  
  
• Rapidly experiment with model architectures and optimization techniques
  
  
• Leverage modern AI tools and frameworks to accelerate development

You will contribute to building League’s next generation of AI capabilities, while partnering with platform and product teams to bring high-impact innovations into production.

In this role, you will:

Model Development & Experimentation

• Design and implement experiments across fine-tuning, distillation, and optimization of small language models (1–10B parameters)
  
  
• Rapidly prototype and evaluate new approaches to model performance, efficiency, and reasoning quality
  
  
• Leverage modern tooling and AI-assisted workflows to accelerate iteration cycles

Applied AI & Systems Integration

• Build applied systems that connect models, data pipelines, and evaluation frameworks
  
  
• Focus on “wiring together” components across model training, evaluation, and deployment workflows
  
  
• Collaborate with engineering teams to transition promising experiments into production environments
  
  

Data & Training Strategy

• Contribute to training data design, including curation, labeling strategies, and synthetic data generation
  
  
• Work with data partners to explore AI-driven insights and improvements to model performance

Evaluation & Model Quality

• Define and run experiments to assess model performance across accuracy, reasoning, and safety dimensions
  
  
• Contribute to building lightweight evaluation frameworks and benchmarking approaches

AI-Native Development Practices

• Actively leverage AI tools (e.g., Copilot, LLM-assisted coding, research copilots) to improve productivity and experimentation speed
  
  
• Document and share workflows that improve how the team builds and evaluates models

Cross-Functional Collaboration

• Partner with Product, Platform Engineering, and AI Orchestration teams to integrate models into real-world use cases
  
  
• Communicate complex technical concepts clearly to cross-functional stakeholders

About you: 

• 5+ years of hands-on experience in applied ML/AI engineering, with a focus on language model development, fine-tuning, or NLP systems.
• Proven track record shipping fine-tuned or distilled LLMs/SLMs (1–10B parameters) to production.
• Deep expertise in PEFT techniques — LoRA, QLoRA, adapter tuning — and model quantization and distillation pipelines.
• Hands-on experience with RLHF/RLAIF, reward modeling, or safety alignment workflows.
• Strong background in data curation, labeling pipeline design, and synthetic data generation.
• Proficiency with model training frameworks and tooling: NeMo, Hugging Face Transformers, Axolotl, or equivalent.
• Experience with model serving stacks: vLLM, Triton, or similar; familiarity with inference optimization techniques.
• Comfort operating on cloud infrastructure (GCP, Vertex AI, AWS) and with GPU resource management.
• Solid understanding of healthcare data privacy and safety requirements: HIPAA, FHIR, clinical ontologies.
• Demonstrated ability to define and own evaluation frameworks — not just build models, but know whether they're working.
• Strong technical communication skills; able to present complex model decisions clearly to cross-functional and executive audiences.
• Bachelor's or graduate degree in Computer Science, Machine Learning, or equivalent experience.

• Use AI tools as part of your daily workflow to enhance productivity, problem-solving, and decision-making (e.g., drafting, analysis, coding, research, or process automation)
• Apply judgment and accountability when using AI by reviewing outputs for accuracy, bias, and quality before use
• Continuously learn and adapt as new AI tools and capabilities emerge, incorporating them into your ways of working
• Identify opportunities to improve how work gets done from personal productivity to team-level workflows by leveraging AI effectively
• Operate with strong data responsibility and security awareness, especially when working with sensitive or regulated information

• Individual Contributors: Use AI to improve personal productivity and quality of output
• Senior ICs / Managers: Integrate AI into team workflows and improve processes
• Leaders: Drive AI adoption at the organizational level and shape how work is done across teams

• Demonstrated experience using AI tools in a practical, responsible way
• Curiosity and openness to experimenting with new technologies
• Ability to balance efficiency with quality and sound judgment

Security-Related Responsibilities

• Compliance with Information Security Policies
• Compliance with League’s secure coding practice
• Responsibility and accountability for executing League's policies and procedures
• Notification of HR, Legal, Compliance & Security of any incidents, breaches or policy violations

Overview

Instacart’s Shopping Experience team is focused on making it fast and effortless for customers to find the right items within a single retailer and complete their order with confidence. As a Senior Data Scientist dedicated to Search, you’ll own the analytics and experimentation strategy that powers how we interpret customer intent and connect it to the most relevant items and retailers.

In this role, you’ll partner closely with Product, Engineering, and Machine Learning to shape the roadmap for search relevance, ranking quality, and latency. Your work will translate complex, noisy signals into clear insights and recommendations that move the metrics that matter—search conversion, order rate, and GTV—while also strengthening downstream experiences like ads and retailer satisfaction.

About the Job

• Own core Search metrics and funnels end to end (e.g., query → impression → engagement → cart adds), including defining guardrails, monitoring performance across platforms and segments, and diagnosing conversion gaps.
• Design, run, and interpret experiments across ranking, retrieval, and search UX (e.g., relevance model changes, query understanding, result layouts), turning ambiguous or conflicting outcomes into crisp, data-driven recommendations.
• Partner with Product, Engineering, and ML to prioritize opportunities, size impact, and influence the roadmap for relevance, quality, and latency improvements that unlock measurable business outcomes.
• Build deep diagnostic analyses by query class, price point, surface, and customer lifecycle to pinpoint where and why Search underperforms and specify concrete changes that will move key outcomes.
• Connect offline model evaluation with online and business metrics by collaborating with ML partners on evaluation design, ensuring model changes reliably improve end-user experience—not just offline scores.
• Improve data quality, instrumentation, and metric definitions for Search so that teams can reason about performance with clarity, consistency, and speed.

About You

You combine rigorous analytics, strong product sense, and clear communication to drive decisive action in a fast-paced environment. You enjoy rolling up your sleeves, collaborating across disciplines, and using experimentation to uncover what truly helps customers find the right items quickly.

Minimum Qualifications

• 5+ years of experience in data science or product analytics, with a track record of impact on consumer-facing products.
• Advanced SQL proficiency, including complex joins and window functions, working with large-scale datasets in modern data warehouses (e.g., Snowflake, BigQuery, Redshift).
• Proficiency in Python or R for analysis, experimentation, and modeling.
• Hands-on experience designing and analyzing A/B tests end to end, including metric selection, power and sample sizing, covariate adjustment, and decision-making under uncertainty.
• Demonstrated ability to define success metrics, decompose ambiguous product problems, and deliver clear, opinionated recommendations to Product and Engineering partners.
• Excellent written and verbal communication skills; able to tailor complex analyses for both technical and non-technical audiences.
• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Mathematics, Economics, Engineering) or equivalent practical experience.
• Comfort using modern AI tooling (e.g., Claude, code assistants, PromptQL) to accelerate analysis, experimentation, and communication while exercising strong judgment on quality and reliability.

Preferred Qualifications

• Experience in search relevance, ranking, recommendations, personalization, or information retrieval (e.g., e-commerce or marketplace search).
• Familiarity with NLP, embeddings, and semantic search, including how to evaluate and iterate on these techniques in production.
• Experience bridging offline evaluation metrics (e.g., NDCG, precision/recall, human evaluation) with online experiments and business outcomes.
• Background in causal inference beyond standard A/B tests (e.g., holdouts, diff-in-diff, quasi-experiments) to measure long-term or cross-surface effects.
• Comfort working across web and native app surfaces, navigating tradeoffs between relevance, monetization, and latency.
• Proven impact improving logging, instrumentation, and metric definitions in complex data environments.

#LI-Remote

We are looking for a Data Platform Engineer to join our Data Engineering team and help build the foundational systems that power Figma’s next generation of AI-driven products and data experiences.

This is a unique opportunity to be an early engineer shaping Figma’s ML and data platform, enabling everything from self-serve analytics to production-grade AI systems. You’ll work at the intersection of data, infrastructure, and machine learning, building scalable systems that empower Data Science, unlock AI capabilities across the company, and bring data and models closer to the product experience.

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:

• Lead work on Figma’s AI data agent to enable self-serve analytics by owning the data-agent layer, building prompt-processing pipelines, instrumenting interactions, and delivering prompt-based usage analytics
• Own and evolve Figma’s ML and data platform, including model serving, feature pipelines, workflow orchestration, CI/CD for models, and production monitoring
• Build product-facing data systems and data products so models and data become first-class components of Figma’s product experience
• Ship platform tooling that enables Data Science teams to deploy, iterate on, and operate models effectively, including feature stores, rollout systems, and observability
• Design and scale infrastructure for AI-assisted and natural language interfaces to data, unlocking self-serve analytics across the company
• Drive cross-functional platform initiatives, aligning data contracts, SLAs, and system design across Data Science, AI/ML, Infrastructure, and Product
• Improve the developer experience for ML and data practitioners through robust abstractions, tooling, and platform capabilities

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

• 5+ years of experience in data platform, infrastructure, or machine learning engineering, with at least 1+ years working on AI or ML systems
• Experience building and operating end-to-end ML systems in production (training, evaluation, deployment, monitoring)
• Strong programming skills in Python or a similar language, with proven ability to build reliable, scalable systems and services
• Experience designing ML infrastructure (model serving, feature pipelines, workflow orchestration) and scalable system architectures
• Proven ability to work cross-functionally and drive projects across Data Science, Engineering, Infrastructure, and Product, with experience in data modeling and data product design

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

• Experience with ML platform tooling such as MLflow, Kubeflow, feature stores, or CI/CD for ML workflows
• Familiarity with LLMs, RAG systems, prompt processing, or AI-native infrastructure
• Experience building self-serve analytics platforms or internal data tools
• Experience with modern data stack technologies such as Snowflake, dbt, or Dagster, and cloud platforms such as AWS
• A strong product mindset and interest in connecting platform work to user and business impact

At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.