Research Engineer in Canada

About the Team The DoorDash Research Fellowship is a 3-month program (extendable to 6 months) looking for Summer and Fall 2026 cohorts, for researchers and engineers who want to work on the hardest applied ML and AI problems in local commerce. Fellows are given the resources, autonomy, and access to real-world operational data needed to pursue ambitious research directions — with the goal of producing work that influences both the field and how DoorDash operates at scale. This program is modeled on the best external research fellowships: fellows are treated as independent researchers, not as junior employees on a product team. You pick the problem (within a set of priority areas), you own the direction, and you publish or ship the outcome. You’re excited about this opportunity because you will receive… Dedicated compute allocation sized to the research agenda — GPU clusters for training and inference budgets for experimentation Full access to DoorDash's research infrastructure — our internal RL stack, training and evaluation pipelines, RL environments built on real operational systems, agent evaluation harnesses, and the tooling our own research teams use day-to-day. Fellows are first-class users, not sandboxed visitors. Access to DoorDash operational data — real-world datasets spanning logistics, merchant operations, consumer behavior, and marketplace dynamics, under appropriate data governance Research mentorship from senior researchers and engineering leaders at DoorDash, plus a named research sponsor for each fellow who meets with you weekly and is accountable for unblocking your work Speaker series featuring leading researchers and practitioners from academia and industry — faculty from top ML programs, research leads from frontier AI labs, and senior operators from across tech. Fellows get dedicated 1:1 time with speakers when possible. A cohort of fellows working alongside you — a small, tight-knit group of researchers tackling different problems but sharing

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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

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. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

About ElevenLabs ElevenLabs is an AI research and product company transforming how we interact with technology. We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms: ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale. ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages. ElevenAPI gives developers access to our leading AI audio foundational models. Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you. How we work High-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy. Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you. AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations. Excellence everywhere: Everything we do should match the quality of our AI models. Global team: We prioritize your talent, not your location. What we offer Innovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible. Growth paths: Joining ElevenLabs means joining a

Overview: Guidepoint seeks an experienced AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization in production

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! We’re looking for a Research Scientist to advance how high-quality data and environments for AI agents are created. You’ll build and optimize pipelines that combine real-world data, automated generation, and human expert input. Working with domain experts, academic partners, customers, and our product and engineering teams, you’ll scale these pipelines to target frontier model performance gaps and expand data and environment diversity. Your work will amplify human knowledge and judgement, enabling experts to create and refine data and agentic environments that strengthens Snorkel’s position as the frontier data lab. This role is ideal for someone who wants to advance frontier AI through data and environment creation and enjoys turning research into reusable, scalable systems. Location: San Francisco, New York, OR REMOTE Main Responsibilities Design, implement, and optimize reusable pipelines that combine AI capabilities with expert judgment to accelerate data and agentic environment creation. Design and run rigorous experiments to validate proof-of-concept approaches, measure their impact on data quality, pipeline efficiency, and model performance, and communic

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. Role Overview As the Okta Research & Design (ORD) Jira Owner & Administrator , nested within the Technical Program Management (TPM) organization, you will define and execute the strategy for how ORD plans, tracks, and reports on engineering work within the full toolchain of Atlassian Jira, Jira Advanced Roadmaps (Plans), Confluence, Rovo, and AI integrations. In this role, you act as a critical bridge between product & technical leadership, agile teams, and cross-functional business units — translating methodology, best practices, and process frameworks into practical workflow improvements that accelerate delivery and reduce manual overhead for a 1,000+ person engineering, product, and design organization. By optimizing tooling configurations, automating reporting, and eliminating fragmented management processes, you will directly accelerate ORD’s developer velocity and strengthen operational efficiency. Core Responsibilities 1. Platform Ownership & Strategic Tooling Direction Strategic Vision: Define, implement, govern an AI-led strategy for utilizing Jira for product planning, tracking, and reporting tooling that supports end-to-end portfolio tracking from high-level corporate objectives down to sprint-level stories. E2E Ecosystem Management: Complete ORD ownership of the toolchain (Jira, Jira advanced Roadmaps, AI integrations, Confluence), overseeing architecture, schema updates, workflow management, screen/notification schemes, cu

This position is based in Vancouver, BC , within Diligent’s Technical Center of Excellence. We are currently hiring candidates who are based in or able to work from Vancouver . Software Engineer — Platform AI Service Levels: Software Engineer II Senior Software Engineer Staff Software Engineer Location: Vancouver Position Overview As a Software Engineer on Diligent's Platform AI team, you'll help design, build, and operate the core services that power AI-driven capabilities across Diligent's global product suite. You'll build secure, scalable, serverless services on AWS that translate AI research and models into commercial-quality, production-ready solutions — enabling customers to derive insights from their governance data. You'll work closely with AI researchers, product managers, and other engineering teams, owning your services end-to-end: architecture, implementation, deployment, and monitoring. The team operates with a strong AI-augmented engineering culture — using AI tools to accelerate coding, testing, debugging, and delivery — while applying sound judgment about when and how to apply them. Key Responsibilities Design and implement secure, scalable, fault-tolerant, high-performing solutions using AWS serverless technology — event-driven, highly observable, and built with infrastructure as code. Collaborate with AI researchers/engineers to translate AI and LLM capabilities into robust, production-grade services, and help other teams integrate them. Build and maintain the pipelines needed to deploy, monitor, and manage AI services at scale — observable, resilient, and cost-effective. Use AI-powered development tools (code assistants, test generation, architecture exploration) responsibly to accelerate delivery and improve quality, always validating outputs. Participate in architecture discussions and design reviews, and contribute to product design by understanding customer problems — especially where AI can offer a breakthrough solution. Work in

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data

About Scale At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations. About the ACE team The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. About This Role This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate t

About Scale AI Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems. Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale. The Opportunity Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges. As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software. Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company. If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in. What You'll Build Frontier AI Systems Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterpri

Overview: Guidepoint seeks an experienced Data/AI Engineer as an integral member of the Toronto-based AI team. The Toronto Technology Hub serves as the base of our Data/AI/ML team, dedicated to building a modern data infrastructure for advanced analytics and the development of responsible AI. This strategic investment is integral to Guidepoint’s vision for the future, aiming to develop cutting-edge Generative AI and analytical capabilities that will underpin Guidepoint’s Next-Gen research enablement platform and data products. This role demands exceptional leadership and technical prowess to drive the development of next-generation research enablement platforms and AI-driven data products. You will develop and scale Generative AI-powered systems, including large language model (LLM) applications and research agents, while ensuring the integration of responsible AI and best-in-class MLOps. The Senior AI/ML Engineer will be a primary contributor to building scalable AI/ML capabilities using Databricks and other state-of-the-art tools across all of Guidepoint’s products. Guidepoint’s Technology team thrives on problem-solving and creating happier users. As Guidepoint works to achieve its mission of making individuals, businesses, and the world smarter through personalized knowledge-sharing solutions, the engineering team is taking on challenges to improve our internal application architecture and create new AI-enabled products to optimize the seamless delivery of our services. This is a hybrid position based in Toronto. What You'll Do: Architect and Build Production Systems: Design, build, and operate scalable, low-latency backend services and APIs that serve Generative AI features, from retrieval-augmented generation (RAG) pipelines to complex agentic systems. Own the AI Application Lifecycle: Own the end-to-end lifecycle of AI-powered applications, including system design, development, deployment (CI/CD), monitoring, and optimization

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. Lyft’s Bikes & Scooters team is developing the future of micro-mobility and we are looking for a Mechanical Engineer to come in and help drive the development of our newest vehicles and sustain our fleet in operation. Responsibilities: Drive design decision by collaborating with product, engineering (EE/ME/FW/SW), reliability, and systems engineering teams Lead post-launch sustaining activities intended to support a smooth transition into production while maintaining high quality standards Derive technical architecture and engineering specifications from product requirements Use analysis to support engineering designs Lead sustaining and continuous improvement projects from concept through release and into field operations Work with GSM and Manufacturing teams to vet supply chain and production partners Prototype; create quick experimental mock-ups and meticulous mechanical models Research technologies and scope development opportunities Develop CAD databases and drawing packages, and drive handoff to manufacturers Support the build and test product development cycle, travel required Test failure analysis and solution validation to complete successful product development Conduct field failure analysis and solution evaluation Lead large projects from idea to positive execution Act on feedback to learn and grow Effectively communicate across cross functional teams to achieve results Experience: BS or MS degree in Mechanical Engineering or related technical field, and 5+ years of related industry experience Experience leading the development of a feature or module of a consumer product Strong foundation in mechanical engineering fundamentals, including solid mechanics, electromagnetics, thermodynamics, and knowledge of basic engineering materials and manufacturing processes Experience in perfo

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. Role Overview As the Okta Research & Design (ORD) Jira Owner & Administrator , nested within the Technical Program Management (TPM) organization, you will define and execute the strategy for how ORD plans, tracks, and reports on engineering work within the full toolchain of Atlassian Jira, Jira Advanced Roadmaps (Plans), Confluence, Rovo, and AI integrations. In this role, you act as a critical bridge between product & technical leadership, agile teams, and cross-functional business units — translating methodology, best practices, and process frameworks into practical workflow improvements that accelerate delivery and reduce manual overhead for a 1,000+ person engineering, product, and design organization. By optimizing tooling configurations, automating reporting, and eliminating fragmented management processes, you will directly accelerate ORD’s developer velocity and strengthen operational efficiency. Core Responsibilities 1. Platform Ownership & Strategic Tooling Direction Strategic Vision: Define, implement, govern an AI-led strategy for utilizing Jira for product planning, tracking, and reporting tooling that supports end-to-end portfolio tracking from high-level corporate objectives down to sprint-level stories. E2E Ecosystem Management: Complete ORD ownership of the toolchain (Jira, Jira advanced Roadmaps, AI integrations, Confluence), overseeing architecture, schema updates, workflow management, screen/notification schemes, cu