Senior Research Scientist in Canada

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? Evaluation is critical to making progress in scaling intelligence. As models continue to become superhuman in many real-world use cases, we must continue to develop new evaluation techniques that accurately reflect what models are already capable of, as well as set the agenda for what future models should be capable of. In this role, you are responsible for creating these next-generation evaluation methods and infrastructure to measure LLM progress. As a Senior Research Scientist, Model Evaluation, you will: Create ambitious new evaluation benchmarks that push the limits of what our models can accomplish. Work on highly cross-functional teams to translate model feedback into trustworthy, repeatable evaluations. Conduct research to advance the state-of-the-art in LLM evaluation methods, including training LLM judges; refining LLM-based data synthesis pipelines; and improving evaluation efficiency. Build scalable and reusable tools for digging into model performance. You may be a good fit if: You enjoy rapidly building prototypes that demonstrate the boundaries of what LLMs are capable of, and you have developed res

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

Director of Engineering, Physical AI Role Overview The Director of Engineering will report to the General Manager of Physical AI, and will be responsible for leading a multi-disciplinary engineering organization. In this senior leadership role, you will own the execution of the Physical AI Data Engine — the platform powering the next generation of Physical AI/Embodied AI. You will collaborate closely with Operations and GTM to guide product direction and help solve the data bottleneck that stands between today's robotics research and real-world deployment. This role requires significant ownership in a fast-paced environment and you will motivate internal teams to set the pace for business growth. Travel will come into play. Key Responsibilities: Set and drive the technical vision across data collection infrastructure, teleoperation systems, ML training pipelines, model evaluation frameworks, annotation tooling, and research Lead a multidisciplinary engineering organization—spanning engineering managers, software engineers, ML engineers, and ML research scientists—while designing the organizational structure, talent strategy, and culture required to scale rapidly without compromising on quality or strategic alignment Maintain exceptional technical and operational excellence by deeply understanding team deliverables, asking incisive questions, identifying slipping standards early, and knowing precisely when to step in Drive cross-functional alignment across Engineering, Operations, and GTM on platform architecture, release processes, and shared priorities Collaborate with researchers and clients to architect and deliver scalable, production-grade data infrastructure tailored for complex robotics workloads Required Qualifications: Bachelor's degree in Engineering, Robotics, Computer Science, or a related technical field 8+ years of engineering experience in fast-paced environments, including 4+ years direct people management demonstrated history of recruiting, mentorin

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

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! About the Team Marketing at Snorkel is growing rapidly and anchored by high-ownership operators who lead independently, align cross-functionally, and consistently deliver outsized results. We partner across Sales, Product, Research, and the executive team to translate complex AI and data value into differentiated positioning, integrated programs, and field-ready enablement that accelerates growth. The culture is high standards, high autonomy, and high collaboration. About the Role Reporting to the Sr. Director of Product Marketing, the Product Marketing Manager, Frontier Labs will own the GTM execution for our frontier lab business. You will partner closely with Research, FDE, and frontier-facing sales teams to translate technical work into research-credible positioning, repeatable sales plays, and high-quality GTM programs that resonate with research and procurement leaders inside frontier labs. You will keep the frontier asset library (battlecards, technical one-pagers, decks, benchmark and eval narratives) sharp against a fast-moving market, and bring competitive and customer insight into every motion. This is a hands-on role for a product marketer who wants

About Us At BGBx , we're driven by a simple idea: breakthrough thinking creates breakthrough impact. As an independent commercial solutions partner to pharmaceutical and life science companies, we bring together strategists, scientists, communicators, creatives, technologists, and data experts to tackle some of healthcare's most important challenges. Our teams work across consulting and communications to help clients shape strategy, launch innovations, engage stakeholders, and drive meaningful results throughout the product lifecycle. The work is complex, fast-moving, and deeply connected to improving lives, creating opportunities for curious minds to make a real difference every day. If you're energized by collaboration, inspired by innovation, and motivated by work that matters, you'll find a place to grow, contribute, and make a meaningful impact at BGBx. Senior Medical Writer Position Overview The Senior Medical Writer must have a proven record of independently and successfully executing the responsibilities and successfully demonstrating the competencies outlined below. They must demonstrate greater independence and ownership compared with the Medical Writer . Please see required experience below. Content Development and Execution: Conducts required research in a timely and proficient manner, utilizing the appropriate resources Develops scientifically accurate, strategically aligned, grammatically correct, and impactful content, from initiation through completion, with input from manager Accurately and efficiently annotates content per brand style guide and AMA rules Assumes accountability for accuracy of work Planning: Understands the product/scientific/therapeutic and competitive space and proactively provides recommendations regarding planned projects to internal team Understands the internal BGB processes and adheres to timelines and procedures, as agreed to by th

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. Our team is dedicated to creating a seamless and secure experience for our riders and drivers, ensuring their identity and data are protected at all times. As a Senior Product Designer, you'll lead the design of solutions that help drivers understand their earnings and get paid securely while protecting our communities from fraud. You will work closely with cross-functional teams, including product managers, designers, engineers, and data scientists, to create intuitive and effective designs on driver payments and complex security challenges. You’ll advocate for a customer-centric approach and thrive in a dynamic, fast-paced environment. From initial ideation through to launch, you'll support projects with interaction, visual, and product thinking skills, helping to define and deliver impactful experiences for our Payment, Identity and Integrity teams. The Opportunity Design features that help drivers understand their earnings, access their pay, and resolve payment issues efficiently Lead end-to-end design for driver earnings and identity verification experiences, from research and ideation through execution Play a critical role in designing solutions that protect our users and enhance their trust in our platform Collaborate with cross-functional partners to design intuitive and effective designs that address unique rideshare driver, identity and fraud challenges Responsibilities: Problem solve, think big, and explore divergent concepts/ideas while understanding how to converge and build iteratively towards your vision. Influence the shape of the product with research and data while executing design work using high quality wireframes, mockups, user journeys, and cross-platform interactive prototypes. Advocate for design by sharing your work and presenting cross-functionally, while being able to

Ignite your curiosity. Solve the unsolvable. At Leidos, we do more than write code—we decode the unknown. Our San Diego-based research and engineering team takes on some of the nation’s toughest defense challenges using advanced signal processing, ocean remote sensing, and high-performance computing. We’re seeking a Software Engineer / Computer Scientist who enjoys solving complex problems and pushing the limits of performance. In this role, you’ll work alongside a multidisciplinary team of scientists and engineers with expertise in hydrodynamics, physics, acoustics, and signal processing to build impactful software that turns massive, complex data sets into meaningful insight. If you are motivated by innovation, energized by collaboration, and excited to see your work support real-world missions, this could be the right opportunity for you. What You’ll Do Collaborate with scientists and engineers to design, develop, and optimize advanced algorithms for next-generation radar, optical, and infrared sensor systems. Build scalable, high-performance backend systems for scientific computing in distributed environments. Integrate, refactor, and improve scientific codebases to increase efficiency and scalability. Translate and optimize existing code for GPU/CUDA acceleration and parallel or distributed execution. Test, document, maintain, and enhance complex software in Linux/Unix environments. Contribute in a collaborative environment that values technical excellence, creativity, and continuous growth. Required Qualifications Bachelor’s degree in Computer Science, Applied Mathematics, Physics, or a related field with 4+ years of backend software development experience, or a Master’s degree with 2+ years of experience. Equivalent experience may be considered in place of a degree. U.S. citizenship and the ability to obtain a Top Secret clearance; active Top Secret clea

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. Okta is The World’s Identity Company. We free everyone to safely use any technology— anywhere, on any device or app. Our Workforce and Customer Identity Clouds enable secure yet flexible access, authentication, and automation that transforms how people move through the digital world, putting Identity at the heart of business security and growth. At Okta, we celebrate a variety of perspectives and experiences. We are not looking for someone who checks every single box - we’re looking for lifelong learners and people who can make us better with their unique experiences. Join our team! We’re building a world where Identity belongs to you. Position Description: As a Senior Research Operations Program Manager at Okta, you will play a crucial role in building and enabling an impactful beta program. Via close collaboration across research, design, product, engineering teams, QA, and release teams, you will programmatically manage cross-functional teams’ research needs. You will proactively build and manage the operations for a beta program, collaborating with other cross functional functions to plan the necessary infrastructure for this programming to be successful, following compliance and governance best practices. In this role, you’ll get to: Lead research operations and panel management for beta programming Work collaboratively across multiple teams to empower Okta staff to carry out impactful research Help manage the general pipeline o

About Scale Scale’s mission is to develop reliable AI systems for the world’s most important decisions. As the leading AI data foundry, we provide the high-quality data and full-stack technologies that power the world’s most advanced models — fueling breakthroughs in generative AI, defense, and autonomous vehicles. We partner with leading enterprises and governments to bring AI into production that performs when it matters most, combining rigorous evaluation with full-stack deployment so our customers can build AI they can trust. About the Team Applied Intelligence Systems (AIS) is part of the Scale Generative AI Platform (SGP), focused on pushing the frontier of what agentic applications can do across diverse enterprise and government use cases. We build the infrastructure and tooling that power agentic AI in production, paired with applied ML research, design, and evaluation to ensure these systems perform reliably at the scale our customers demand. AIS spans multiple workstreams — agent evaluation and oversight, orchestration and tool-use infrastructure, model and systems optimization, and applied research on new agent capabilities — and this role is not scoped to any single one of them. We’re growing fast, with increasing traction across both commercial and public sector customers, and we’re just getting started — this team will define what dependable, production-grade agentic AI looks like. About the Role As a Staff Machine Learning Research Engineer, you will operate across the full breadth of AIS’s technical needs — wherever the hardest ML problem in agentic AI happens to be that quarter. This could mean training and fine-tuning models, designing evaluation and observability systems, building improvement loops from production data, prototyping novel agent architectures, or designing internal systems and tooling that boost productivity across teams. You’re not tied to one team’s roadmap; you’re expected to move to where the technical leverage is highest, and t

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with leading enterprises and government organizations to accelerate their AI initiatives through our data annotation platform, generative AI solutions, and enterprise AI capabilities. About the General Agents Team The General Agents team, part of Scale’s Enterprise organization, builds robust general agents for customer use cases and applications. The team sits at the intersection of frontier agent development and real-world deployment, translating state-of-the-art reasoning and agentic capabilities into reliable, production-grade systems that drive real economic value. Our agents are scalable systems built around recurring enterprise problem domains, with a strong emphasis on generalization, extensibility, and deployment across many customers. About the Role As a Senior/Staff Machine Learning Engineer (MLE) on the General Agents team, you’ll play a critical role in designing, building, and deploying production-ready AI agents that solve high-impact enterprise problems. You will work across the full agent lifecycle—from model and system design to evaluation, deployment, and iteration—bridging cutting-edge agentic techniques with the constraints and requirements of real customer environments. You will: Design and implement end-to-end agent systems that combine LLM reasoning, tool use, memory, and control logic to solve recurring enterprise use cases. Build scalable, reliable agent architectures that can be deployed across many customers with varying data, tools, and constraints. Develop evaluation frameworks, datasets, environments, and metrics to measure agent performance, reliability, and business impact in production settings. Collaborate closely with product managers, customers, data annotators, and other engineering teams to translate enterprise requirements into robust agent designs. Productionize frontier agent techniques (e.g.,

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

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

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