Ai Research Fellowship in Canada

Scale’s ML platform (RLXF) team builds our internal distributed framework for large language model training and inference. The platform has been powering MLEs, researchers, data scientists and operators for fast and automatic training and evaluation of LLM's, as well as evaluation of data quality. Scale is uniquely positioned at the heart of the field of AI as an indispensable provider of training and evaluation data and end-to-end solutions for the ML lifecycle. You will work closely across Scale’s ML teams and researchers to build the foundation platform that supports all our ML research and development. You will be building and optimizing the platform to enable our next generation of LLM training, inference and data curation. If you are excited about shaping the future AI via fundamental innovations, we would love to hear from you! You will: Build, profile and optimize our training and inference framework Collaborate with ML teams to accelerate their research and development and enable them to develop the next generation of models and data curation Research and integrate state-of-the-art technologies to optimize our ML system Ideally you’d have: Strong excitement about system optimization Experience with multi-node LLM training and inference Experience with developing large-scale distributed ML systems Strong software engineering skills, proficient in frameworks and tools such as CUDA, Pytorch, transformers, flash attention, etc. Strong written and verbal communication skills and the ability to operate in a cross functional team environment Nice to haves: Demonstrated expertise in post-training methods &/or next generation use cases for large language models including instruction tuning, RLHF, tool use, reasoning, agents, and multimodal, etc. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the positi

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r

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.,

We are looking for a Portfolio Research Analyst to join our fast-paced and entrepreneurial Quantitative Equity Team! We are a high-performance team embedded in a top-performing quantitative equity fund that manages over $78+ billion USD in financial assets. We combine quantitative research with leading-edge technology to develop our unique algorithmic investment strategies. A culture of innovation, growth and success through collaboration and mutual respect has enabled us to deliver top tier performance for over two decades. This is a role within the Portfolio Construction group responsible for the construction of optimal portfolios and desired trades for those portfolios. You will be contributing to the ongoing advancement of our in-house equity portfolio optimization framework that directly drives our daily investment decisions for delivering exceptional portfolio performance over the long term. You will possess an understanding of the key drivers of equity portfolio construction, including equity forecasts, risk management, and transaction cost management. We are based in beautiful Vancouver, Canada; our team embraces the lifestyle and activities that life in Vancouver awards. What You Will Do This is an exciting role for an individual who is passionate about quantitative research and wants to apply a disciplined and scientific approach to portfolio construction. You will work with key decision makers on the team and have a broad range of responsibilities, including: Research and development – Conduct projects to enhance the portfolio optimization solutions by applying a variety of skills and techniques in finance, mathematical optimization, and statistics. Portfolio oversight – Monitor portfolio characteristics and ensure consistency with investment strategy and guidelines. Performance analysis – Conduct in-depth portfolio performance attribution to support decision making, performance evaluation, idea 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. Lyft is seeking a qualitative User Experience Research Intern to join our team, which aspires to elevate the user experience for our drivers and riders across 300+ cities nationwide. You will conduct research studies, as well as participate in studies alongside more senior researchers from which you’ll gain strong mentorship. You will partner with Design, Product Management, Analytics, and Engineering in order to derive deep insights about our users’ behaviors and attitudes, and communicate results and actionable recommendations across the company. Interns contribute to user-facing products, working side-by-side with top User Experience Research team members in the industry while having autonomy from the get-go. Lyft fosters a collaborative environment in the office, so there's always a sharp mind eager to hear about your next idea. So what's yours? Responsibilities: Design and conduct studies across key Lyft product areas -- independently and in conjunction with more senior researchers. You will utilize methods such as ethnographic & field research, diary studies, surveys, user/usability testing (remote and in-person), guerrilla research, and any other methods you find impactful Review, analyze, and communicate qualitative and/or quantitative data to generate tactical and strategic insights, as well as actionable recommendations which drive product innovation and design improvements for users Experience: Currently pursuing a Master's or PhD degree in Human-Computer Interaction, Anthropology, Design, Psychology, Cognitive Science, or a related field from a university in Canada with a graduation date between December 2027 and Summer 2028 (required) Available during Summer 2027 for an internship in Toronto Extraordinary organizational skills and meticulous eye for detail Str

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. Research at Stripe Stripe’s mission is to increase the GDP of the internet and expand economic access globally. We design tools and infrastructure to help our users start, run, and scale an online business from anywhere in the world. We believe there are too many barriers to doing business on the internet and that opportunities are not equally distributed around the world. We also believe that building and growing a business online is a problem rooted in code, language, and design, not finance. That’s where you come in. We’re looking for an experienced UX Research Manager to join our growing UX Research team and help build, coach, and mentor a growing and highly skilled group of researchers. About UX research and the role The UX Research team is part of Stripe’s Design team. It works across brand and product initiatives to deliver products and experiences that meet user needs. Since Stripe’s main audience is people who build products, we take pride in creating user-friendly, user-focused experiences. In addition to conducting primary research, we enable other Stripes, including engineers, product managers, designers, and operations teams, to learn and apply research skills to global problems. You will help shape research as a core competency across Stripe and define how we put users first in our research. What you’ll do As a UX Research Manager, you will use your people-management and research expertise to lead a team of researchers that collaborates w

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

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

We are looking for research interns to join our Quantitative Equity team for 4 to 8 months starting in January or May 2027. We are a top-performing quant fund that manages over $111 billion in financial assets, with a track record spanning more than two decades. As a privately owned firm, we take a long-term perspective, investing in lasting business success and the long-term careers of our people. What You Will Do Investing presents a rich set of research problems that you will explore in this role. Quantitative Researchers lead the development of our investment models and strategies. As an intern, you will work on a real investment research project that requires thinking deeply about the factors that determine business success and modeling the complex dynamics of capital markets, including how information is created, interpreted and reflected in prices. Y our work will have a direct impact on investment outcomes. You will own your research project from beginning to end, including idea generation, signal construction, backtesting and calibration. There is plenty of opportunity to collaborate with your peers and receive mentorship from senior members of our research team. Our team works with: State-of-the-art techniques, including reinforcement learning, large language models, AI agents and econometric methods Large financial and alternative data Advanced technologies, such as high-performance computing infrastructure and custom research systems What You Bring Exceptional quantitative and technical ability : a strong foundation in mathematics, statistics, computer science, economics, finance or a related discipline An interest in finance: an interest in the domain is essential ; an understanding of capital markets and the drivers of business success is valuable but not required Evidence of exceptional ability and achievement: demonstrated through academic, professional, research, competition, entr

We are looking for researchers to join our Quantitative Equity team. We are a top-performing quant fund that manages over $111 billion in financial assets, with a track record spanning more than two decades . As a privately owned firm, we take a long-term perspective, investing in lasting business success and the long-term careers of our people. What You Will Do Investing presents a rich set of research problems that you will explore in this role. Quantitative Researchers lead the development of our investment models and strategies. This requires thinking deeply about the factors that determine business success and modeling the complex dynamics of capital markets, including how information is created, interpreted and reflected in prices . Y our work will have a direct impact on investment outcomes. You will own your research projects from beginning to end, including idea generation, signal construction, backtesting and calibration. There is plenty of opportunity to collaborate with your peers and receive mentorship from senior members of our research team. Our team works with: State-of-the-art techniques, including reinforcement learning, large language models, AI agents and econometric methods Large financial and alternative data Advanced technologies, such as high-performance computing infrastructure and custom research systems What You Bring Exceptional quantitative and technical ability : a strong foundation in mathematics, statistics, computer science, economics, finance or a related discipline An interest in finance: an interest in the domain is essential ; an understanding of capital markets and the drivers of business success is valuable but not required Evidence of exceptional ability and achievement: demonstrated through academic, professional, research, competition, entrepreneurship, or other accomplishments We welcome applications from candidates with different levels of experience, including

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? To have the opportunity to collaborate with Cohere researchers and tools on designing and implementing novel research ideas and shipping state-of-the-art models to production. We have openings in teams covering base model training, retrieval augmented generation, data and evaluation, safety, and finetuning, to name a few; and we are open to receiving intern applications in any research area relating to LLMs to broaden your research connections while obtaining deep experience in a growing AI startup. Please Note: To be eligible for a Research Internship, you must be currently pursuing a PhD in Machine Learning, NLP, or a related discipline. You need to be available for a full-time internship that lasts for 4-6 months. As a Cohere Research Intern, you will: Conduct cutting-edge machine learning research, building and training large language models. Focus on research projects aimed at expanding the frontier of knowledge in language modelling and associate areas such as evaluation, multimodal models, optimisation etc. Disseminate your research results through the production of publications, datasets, and code. Contrib

JLL empowers you to shape a brighter way . Our people at JLL are shaping the future of real estate for a better world by combining world class services, advisory and technology for our clients. We are committed to hiring the best, most talented people and empowering them to thrive, grow meaningful careers and to find a place where they belong. Whether you’ve got deep experience in commercial real estate, skilled trades or technology, or you’re looking to apply your relevant experience to a new industry, join our team as we help shape a brighter way forward. Research Analyst – JLL What this job involves: The Research Analyst will join JLL's San Francisco Research team to deliver market intelligence that sets JLL apart. You will analyze San Francisco's industrial, office, and flex markets alongside the economic drivers that shape them. This role combines direct client engagement with hands-on data analysis, positioning you at the intersection of urban economics and commercial real estate. You will grow from foundational market research into automated workflows, quantitative modeling, and independent analysis—building both analytical rigor and technical capability. If you're curious about what drives markets and ready to become data fluent while mastering local real estate dynamics, this role offers a clear path forward. What your day-to-day will look like: Develop expertise on San Francisco's economy, industry composition, demographics, and commercial real estate market to identify trends and emerging opportunities Maintain comprehensive market coverage by tracking significant leasing activity, tenant movements, development projects, sales transactions, and ownership changes Meet regularly with clients and internal teams to present market insights, conditions, and forecasts Produce quarterly reports on San Francisco market

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