Product Analyst in Canada

About the Role: As a Staff Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi. A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine. You will improve the way we deploy and operate our services and even contribute to open-source projects. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams. Responsibilities: Design and build scalable, high throughput, and low latency distributed systems using Scala Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art. Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc. Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi. Your Background: Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM b

About the Role: Tubi is seeking a highly skilled and experienced Senior QA Automation Engineer to lead quality assurance initiatives for our cutting-edge streaming and AI-driven product features. This pivotal role involves ensuring exceptional end-to-end user experiences, robust streaming playback, and the accuracy and integrity of our AI/ML features across web, mobile, and OTT platforms. We're looking for a candidate with a strong background in streaming QA and deep technical knowledge of media workflows. You'll be instrumental in collaborating with engineering, product, and data science teams to define comprehensive QA strategies that guarantee both functional excellence and data-level quality. This is a hybrid role based out of our Toronto office. You must be willing to travel to our Toronto office three days/week. What You'll Do: Design and lead test strategies for streaming workflows, playback systems, and AI-powered features. Test across platforms (web, mobile, and connected TV) to ensure functional parity and playback stability. Validate streaming performance—including ABR logic, encoding pipelines, and DRM integrations—under diverse real-world conditions. Debug with precision using tools like Charles Proxy, Chrome DevTools, ADB, and Xcode. Collaborate with data and ML teams to validate AI model updates, recommendations, and personalization accuracy. Leverage AI-assisted QA tools to enhance regression coverage, UI validation, and anomaly detection. Contribute to automation and CI/CD frameworks, driving faster, more reliable releases. Help drive a shift-left testing approach by engaging early in the software development lifecycle, partnering with product managers, engineers, and data scientists to identify quality risks, define test strategies, and ensure testability during requirements and design phases. Oversee QA deliverables for multiple concurrent releases and ensure seamless sign-off for production launches. Monitor live environments for playback or reco

Who We Are HP IQ is HP’s new AI innovation lab. Combining startup agility with HP’s global scale, we’re building intelligent technologies that redefine how the world works, creates, and collaborates. We’re assembling a diverse, world-class team—engineers, designers, researchers, and product minds—focused on creating an intelligent ecosystem across HP’s portfolio. Together, we’re developing intuitive, adaptive solutions that spark creativity, boost productivity, and make collaboration seamless. We create breakthrough solutions that make complex tasks feel effortless, teamwork more natural, and ideas more impactful—always with a human-centric mindset. By embedding AI advancements into every HP product and service, we’re expanding what’s possible for individuals, organisations, and the future of work. Join us as we reinvent work, so people everywhere can do their best work. About the Role HP IQ is shaping the future of next‑generation experience for HP Customers, and we’re looking for a Program Manager who can help drive that mission. This role sits at the heart of how our teams build, validate, and deliver AI‑powered experiences with exceptional quality and developer efficiency. You’ll lead programs that strengthen QA processes, enhance developer workflows, and accelerate engineering velocity across HP’s AI product portfolio. Success in this role requires a blend of technical fluency, structured program leadership, and the ability to communicate clearly across—and up—the organization. Responsibilities Program Leadership & Execution Drive end‑to‑end planning, execution, and delivery of QA and Developer Experience programs within the HP IQ organization. Build and maintain program roadmaps, milestones, and KPIs that align with organizational priorities. Identify risks, dependencies, and cross‑team impacts early, and lead mitigation strategies. Ensure consistent alignment across engineering, QA, product, data science, and partner teams. Quality & Developer

Must be based in Vancouver The role We're hiring a dedicated data engineer to own the production data platform that our delivery, product, and engineering teams run on; designing integrated, governed data pipelines and delivering automated reporting, AI-assisted workflows, and predictive signals on top of them. You'll write production code, design systems, own CI/CD, and be accountable for the correctness of data that leaders make decisions on. What you'll do Design and operate our cloud data platform: ingestion, transformation, orchestration and serving. Integrate data from across the business (delivery tooling, CRM, product telemetry, finance, support and customer feedback systems) with shared identifiers, data contracts and lineage. Build automated and continuously refreshed reporting so teams manage by exception rather than chasing status. Connect approved AI agents to governed data with structured outputs, provenance, guardrails and human approval in the loop. Build feature pipelines and the MLOps controls behind predictive use cases: tests, versioning, promotion gates and drift monitoring. Own the engineering standards for data: testing, observability, environment promotion, PII classification and access control. What you'll bring Strong software engineering fundamentals: production-quality code, API and interface design, testing discipline, systems design. Real experience building and operating production data platforms on a cloud warehouse or lakehouse (Snowflake and AWS preferred) with dbt and a modern orchestrator. Practical AI tooling experience: something shipped, not prototyped. LLM-backed classification, extraction or structured-output pipelines; agent and tool-calling workflows; retrieval; evals. You can reaso

At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. Scale Frontier Data is the organization behind the training and evaluation data that frontier labs depend on. We build the systems, tooling, and expert workflows that turn hard human expertise into signals that models can learn from, across reasoning, coding, agentic tool use, and domain expertise. About our Customer Platform team: Our Customer Platform Team plays a pivotal role in integrating our platform with external systems and ensuring seamless, reliable connectivity for both internal users and customers. As the leader of this team, you’ll drive the strategy, architecture, and development of our connectivity solutions, focusing on API integration, distributed systems, and a robust data platform. Your role will be crucial in maintaining and enhancing our platform’s ability to meet the needs of both our internal and external stakeholders. Responsibilities: Own large areas within our product Comfortable working cross functionally, whether that be internal or external customers Build features end-to-end: front-end, back-end, system design, debugging and testing Deliver experiments at a high velocity and level of quality to engage our customers Work across the entire product lifecycle from conceptualization through production Influence the culture, values, and processes of a growing engineering team Inspire and mentor less experienced engineers Collaborating with cross-functional teams to define, design, and ship new product features and experiences. Requirements: At least 7-10 years of relevant experience is preferred Track record of shipping high-quality products and features at scale Desire to work in a very fast-paced environment Abil

About the Team The Storage teams build and operate online stateful systems and abstractions that are reliable, efficient, secure and easy to use for DoorDash Engineering. The teams are responsible for understanding Product Engineering’s evolving needs and developing platform and infrastructure capabilities to serve them. The team currently supports CockroachDB, Cassandra, Kafka and Redis as well as data abstraction services to reduce the complexity of interacting with storage systems for Product Engineers. About the Role The Storage team is building and operating a high-performance, scalable, and reliable data abstraction layer that optimizes both efficiency and reliability. Our goal is to create a platform that manages itself and fades into the background—empowering engineers to focus on delivering product experiences our customers love. This role is available across two teams within Storage, each solving unique and high-impact challenges: One team is building the orchestration layer for DoorDash’s storage platform—unifying lifecycle management, operations, and self-serve APIs for databases and streaming systems, turning complex, stateful infrastructure into reliable, developer-friendly services used across the company. One team builds and operates the distributed data platform powering DoorDash's largest stateful workloads -- including Cassandra, which backs critical product surfaces across DoorDash, Wolt, and Roo. You'll design high-throughput data abstractions, smart clients, and platform services that make distributed data reliable and easy to work with at multi-petabyte, multi-million-QPS scale, with opportunities to go deep on distributed systems internals and contribute to the open-source Cassandra ecosystem. If you're passionate about distributed systems, developer experience, and building foundational infrastructure at scale, we'd love to hear from you. You must be located in San Francisco, Sunnyvale, Seattle, or the New York Metro Area for this hybrid pos

Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk. The Staff Software Engineer Opportunity Passkeys, powered by FIDO2 WebAuthn, are revolutionizing how people authenticate—bringing us into a passwordless future that’s more secure and seamless than ever before.At Okta, we’re on a mission to help enterprises and consumers embrace this transformation. We’re building cutting-edge phishing-resistant authenticators and passkey solutions that make security stronger while making life easier for users. Our products empower businesses to leave passwords behind and defend against modern threats with innovative, user-friendly technology. We are looking for a Staff Software Engineer to join the Passwordless team. As a Staff Engineer, you will be a technical leader, making large, independent contributions and shaping the future of how millions of users access technology securely. This is a role for an engineer who thrives on solving ambiguous problems and taking ownership of end-to-end solutions. You will not only execute on complex technical challenges but also influence the team's direction, mentor other engineers, and proactively identify opportunities to improve our products and processes. If you are passionate about building highly reliable, scalable systems and want to define the future of passwordless authentication, we’d love for you to join us. What you’ll be doing Partner closely with product, design, and other cross-functional stakeholders to own problem spaces and ensure we are building the right solutions fo

A Test Program Manager (or Test Engineering Program Manager) leads cross-functional teams to define, plan, and execute product testing strategies, ensuring quality from development to launch. They manage test schedules, budgets, and vendor relations while driving bug resolution and reporting status to leadership. Apple +4 Key Responsibilities Strategy & Planning: Define comprehensive end-to-end testing strategies, covering functional, regression, and system testing. Cross-Functional Leadership: Coordinate with software, hardware, and RF test engineers to align testing with product development. Execution & Monitoring: Drive test readiness reviews, monitor test execution, and manage defect reporting. Vendor & Budget Management: Manage test suppliers, vendors, and development budgets. Risk Management: Proactively identify project risks, inter-dependencies, and bottlenecks to ensure on-time delivery. Apple +6 Required Skills & Qualifications Technical Proficiency: Familiarity with test technologies, CICD, and automation tools. Project Management: Experience with software development lifecycles (SDLC) and complex product testing. Communication: Excellent leadership, presentation, and conflict-resolution skills. Education/Experience: Often requires a degree in Engineering (Software/Electrical) and experience in testing or program management. Apple +4

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . With more than 500 million users around the world and 300 billion ideas saved, Pinterest Machine Learning engineers build personalized experiences to help Pinners create a life they love. With just over 4,000 global employees, our teams are small, mighty, and still growing. At Pinterest, you’ll experience hands-on access to an incredible vault of data and contribute large-scale recommendation systems in ways you won’t find anywhere else. What you’ll do: Build cutting edge technology using the latest advances in deep learning and machine learning to personalize Pinterest Partner closely with teams across Pinterest to experiment and improve ML models for various product surfaces (Homefeed, Ads, Growth, Shopping, and Search), while gaining knowledge of how ML works in different areas Use data driven methods and leverage the unique properties

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Product Education team designs, develops, and launches learning experiences for Lyft customers in the in-app and web Learning Center. We partner with stakeholders across Lyft to make sure customers get accurate, timely information — from in-app safety features to tax season tips to five-star guidance — reaching hundreds of thousands of customers across the US and Canada. Our ~200 tutorials support 25M+ enrollments a year, and we work closely with the Learning Platform product and engineering teams to build the features that support customer learning at scale. We're looking for a Senior Education Content Producer to own visual asset creation and accuracy for the Learning Center. Most of your time will be spent on video editing and motion graphics. You’ll design, create and edit new videos, animations and images, and keep our existing library accurate as the underlying product is constantly evolving. You'll also need solid producer skills: pitching and managing external vendors/agencies, and running the occasional small-scale shoot. You'll work alongside our other Content Producer, who also owns asset creation and updates, and our Learning Experience Designers, who write and structure tutorial content. Together, you'll make sure every customer-facing tutorial looks and feels like Lyft, and stays that way as the product changes. Responsibilities: Visual Asset Creation & Accuracy Using the Adobe Creative Suite and Figma, edit and animate new video, motion graphics, and image assets from concept through final delivery Own the day-to-day health of our visual asset library: auditing, updating, and troubleshooting images, live-action video, UI walkthroughs, and animations across dozens of tutorials Track versioning closely as the underlying product changes, proactively catching and

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The strongest enterprise and mid-market marketing doesn't lead with a product — it leads with the problem a buyer already has. A hospital administrator isn't looking for "Lyft Concierge"; they're looking to reduce missed appointments. An auto dealer principal isn't looking for a rideshare product; they're looking to keep loaner logistics from costing them revenue. We are in the process of revising our go-to-market for Lyft Business to organize around these audiences and their transportation problems, with Concierge, Lyft Pass, Business Profiles, and our Business Travel products positioned as the answer to a clearly named pain point by customer profile. We're hiring an Industry Marketing Manager to build that audience-first structure for our priority verticals, starting with Healthcare and Automotive , across both mid-market and enterprise segments. You'll own the vertical narrative and the content, demand generation strategy, and enablement that will drive marketing-attributable revenue. The primary function of this role is to build and lead vertical-specific go-to-market (GTM) motions for our mid-market and Enterprise business — bringing together vertical-specific content, demand generation, and sales enablement into a coherent, audience-first strategy. Responsibilities: Own vertical strategy and integrated programs Design and execute large, orchestrated tentpole programs for our priority verticals (no more than 2 per quarter) — multichannel activation spanning digital, live events, paid media, social, and press — that bring our value proposition and industry point of view to life for a defined buyer (e.g., hospital CFO, healthcare operations leader, dealer principal/service manager). Build and maintain a thought leadership agenda for each prioritized vertical: original research, proof p

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. The Lyft Business Product Platform team builds the systems and experiences that power Lyft's B2B products — enabling companies, organizations, and their employees to seamlessly access Lyft's transportation network. We sit at the intersection of product and platform, owning both the customer-facing features and the underlying infrastructure that makes them reliable at scale. Our work directly impacts how businesses integrate with Lyft, how admins manage their programs, and how millions of riders get where they need to go. Responsibilities: Drive architecture and technical design for systems that are highly available, scalable, and built to last — not just for today's requirements but for where the product is heading Own features end-to-end: from shaping the technical spec and design through to production rollout and operational health Think critically about how AI capabilities can be incorporated into Lyft Business products to improve the experience for business admins and riders — and bring that perspective into roadmap and architecture conversations Make well-reasoned trade-off decisions and communicate them clearly to peers, leads, and cross-functional partners Write clean, well-tested, maintainable code and hold a high bar for the same in code reviews Partner across engineering, product, and design to align on direction and get buy-in on technical approaches Proactively engage in incident response, contributing both to resolution and to long-term reliability improvements Grow the team's technical culture through design reviews, tech talks, and mentorship Experience: 5+ years of software engineering experience, with a track record of designing and shipping production systems at scale Strong system design instincts — you can reason through distributed systems trade-offs, identify failure modes, and

About Us Twitch is the world’s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day. We’re about community, inside and out. You’ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We’re on a quest to empower live communities, so if this sounds good to you, see what we’re up to on LinkedIn and X , and discover the projects we’re solving on our Blog . Be sure to explore our Interviewing Guide to learn how to ace our interview process. About the Role As a Senior Label Relations Manager on the Twitch Music team, reporting to the Director of Music Relations & Licensing, you will be key to building, strengthening, and maintaining relationships between Twitch and our music partners (labels and other third-party strategic partners). The Twitch Music team bridges the gap between Twitch, the music industry, and our streamers. In addition to furthering existing relationships, you will be pivotal in creating new relationships within the music and DJ communities, as well as developing new business partnerships and deal structures. This role will be highly cross-functional, working with both internal and external business partners. Internally, this role will be working across Operations, Programming, Product, Engineering, Legal and Finance to support the overall Twitch Music strategy. The role will require travel and may require evening attendance at industry events and shows. You can work in Los Angeles, CA or New York City, NY. You Will: Develop and leverage relationships with external partners (labels, artists, managers, third parties) to deepen engagement with the Twitch service, including by coordinating efforts across multiple external stakeholders. Act as an ambassador and advocate for Tw

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 Large, complex businesses on Stripe have historically had to create a new Stripe account for each global entity or business unit—making it difficult to unify reporting and manage payment operations across all accounts. Our customers want a way to manage these accounts under one umbrella so they can operate at scale more efficiently. We are responsible for building Organizations, which allows merchants to effectively and centrally manage their businesses across multiple Stripe accounts. As Stripe continues to grow its suite of product offerings beyond payments, Organizations will unlock a new phase of growth for Stripe. We will do this by enabling our platforms and businesses to model their complex businesses and distribute all of Stripe’s products to their end users. You can read more about what we are working on here (our Stripe Blog). What you’ll do As a leader on the User Auth Experience team, you will help shape the team’s vision and roadmap, guide and mentor your peers, and lead by example. Authentication, Login, and general Account Security experiences are deeply cross-cutting areas at Stripe with critical security, safety, and quality considerations. You will work with many partner teams: peer engineering organizations to build robust/reusable/standardized access controls, as well as non-engineer groups to shape the security, beauty, and usability of the end-to-end journey of Stripe account authentication. You’ll pla

About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! In September 2026 we raised a $350 million Series E at a $3.5 billion valuation , and we are scaling our engineering and research teams to meet demand. The role Frontier AI data is expensive to make and hard to measure. Every task we deliver is tested against the strongest models, often through many long-running agent rollouts. Your job is to make that process faster, cheaper, and more rigorous with ML and AI You will be one of the early members of ML & Research Engineering at Snorkel. You will study how frontier-grade data is generated and evaluated, form hypotheses, validate them against real production data, and ship the winners at scale. You will shape the discipline's direction, its standards, and the team that grows around it. What you'll work on Efficient agentic evals. Cut the cost of long-horizon agent evaluation with adaptive sampling, statistically grounded early stopping, model cascades, caching, and cheap-first gating. AI model routing. Route every eval and judge call to the cheapest model that clears the quality bar, with fallback, monitoring, and cost attribution. Fine-tuned small models. Fine-tune and serve open-weight models (LoRA and other