Research Internship 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? 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

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

A World-Changing Company Palantir builds the world’s leading software for data-driven decisions and operations. By bringing the right data to the people who need it, our platforms empower our partners to develop lifesaving drugs, forecast supply chain disruptions, locate missing children, and more. The Role Software Engineers at Palantir build software at scale to transform how organizations around the world use data. As a Software Engineer Intern, you’ll have an opportunity to grow more quickly than you ever envisioned, as you contribute high-quality code directly to Palantir Gotham, Palantir Foundry, or Palantir Apollo: products that are deployed at some of the most important institutions across the public and private sectors. You'll create features used by research scientists, aerospace engineers, intelligence analysts, and economic forecasters, in countries around the world. Palantir's Product Development organization is made up of small teams of Software Engineers, each focusing on a specific aspect of a product. For example, you might join a team that builds a Foundry front-end application, or a component of the Gotham release infrastructure. We encourage communication and collaboration among teams to share context, skills, and experience, so you'll learn about many different aspects of each product. Core Responsibilities As a Software Engineer, you are involved throughout the product lifecycle - from idea generation, design, and prototyping to execution and shipping while also being paired with a mentor dedicated to your growth and success. You'll collaborate closely with technical and non-technical counterparts to understand our customers' problems and build products that tackle them. One of the most effective ways to understand what our users need is to meet them. You may receive an opportunity to tour the assembly line at an auto-manufacturer or join a counter-terror analyst at their desk to really understand their mission and difficulties. SWE

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? Ship state of the art models to production. Design and implement novel research ideas. Build elegant training/deployment pipelines. Join us at a pivotal moment, shape what we build and wear multiple hats as an intern! Our recruitment process will begin in the upcoming weeks, and we will be carefully reviewing applications and assessing potential candidates for our internships. Should we find a suitable match with your qualifications and our requirements, we will be in touch to discuss the opportunity further and to advance your application to the next stage Please Note: To be eligible for this position you should be a student currently enrolled in a post-secondary program, available for a full-time 3-6 month internship, co-op, or research work term. As a Machine Learning Intern, you will: Design, train and improve upon cutting-edge models. Help us develop new techniques to train and serve models safer, better, and faster. Train extremely large-scale models on massive datasets. Explore continual and active learning strategies for streaming data. Learn from experienced senior machine learning technical staff. Work c

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a Masters degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have

About the Team DoorDash is building the world’s most reliable on-demand logistics engine for delivery! We’re looking for machine learning engineer interns to join our fast-growing engineering team to help us develop a 24x7 global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers. About the Role As a Machine Learning Engineer intern at Doordash, you’ll work on tackling new challenges in machine learning and artificial intelligence. You’ll conduct research that can be applied across Doordash engineering teams and engage in external collaborations and mentoring, while also performing research in any of the following areas: Auction, Game theory, Recommender systems, Ranking, AdTech, Computer Vision, Causal Inference, and Big data analytics. We offer a 12-week summer internship program in our San Francisco, Sunnyvale, New York, or Seattle offices. You’re excited about this opportunity because you will… Use cutting-edge research in ML/AI, NLP, RecSys, Ranking, Computer Vision, Causal Inference, Ad Tech, Graph analysis to solve real-world problems across discovery, ads,forecasting, fulfillment and search experiences at Doordash. Contribute and execute on research ideas that can be applied and used to improve product experience at Doordash. Collect, analyze, and synthesize findings from data and use these insights to build relevant ML models. Write clean, efficient, and sustainable code We’re excited about you because you… Are working towards a PhD degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field and are graduating between Fall 2027 & Summer 2028 Have a mastery of at least one systems languages (Java, C++, Python, Kotlin, GoLang) or one ML framework (Tensorflow, Pytorch, MLFlow) Have experience in research and in solving analytical problems Are a strong communicator and team player. Have a passion for applied ML and the Doordash product Ideally have work

About the Team At DoorDash, design shapes how millions of people connect with their local economy and we put our customers at the center of our product strategy. Our design team crafts thoughtful experiences across the ecosystem, from consumers ordering their favorite meals to merchants growing their businesses and Dashers delivering with care. About the Role Design is changing faster than at any point in the last decade, and we’re building the team that defines what comes next. As a Product Design Intern, you’ll get to work on real projects that impact our customers, merchants, and Dashers. You’ll collaborate with product, research, data, and engineering to prototype your concepts, test with real users, and ship improvements to millions of users. You will have the opportunity to join one of our core teams: Consumer, Merchant, Dasher, Ads & Promos, or Customer Experience & Integrity. Based on your skills, interests, and business priorities you’ll be paired with a dedicated manager and supported by a community of designers passionate about learning and helping each other grow. This will be a 12-week summer internship program hosted onsite at our San Francisco or New York City offices. There will be relocation support as needed. You're excited about this opportunity because you will… Drive a real project from early explorations to polished, shipped work that reaches millions of users. Use AI throughout your process — exploring divergent directions, building high-fidelity prototypes, and pressure-testing ideas — while helping shape how our product becomes smarter, more intuitive, and more human. Collaborate closely with designers, engineers, PMs, and researchers to identify opportunities and ensure high-quality implementation. Learn from a dedicated manager and a community of peers in a fast-paced, mission-driven environment that values curiosity, craft, and collaboration. We're excited about you because… You’re currently pursuing a degree in de

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

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

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 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

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

Scale Labs, Research Scientist — Agent Robustness As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist working on Agent Robustness you will work on the fundamental challenges of building AI agents that are safe and aligned with humans. For example, you might: Research the science of AI agent capabilities with a focus on how they relate to safety, risk factors, and methodologies for benchmarking them; Design and build harnesses to test AI agents’ tendency to take harmful actions when pressured to do so by users or tricked into doing so by elements of their environment; Design and build exploits and mitigations for new and unique failure modes that arise as AI agents gain affordances like coding, web browsing, and computer use; Characterize and design mitigations for potential failure modes or broader risks of systems involving multiple interacting AI agents. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be comfortable building and leveraging agent scaffolding, designing evaluation harnesses, an

Scale Labs, Research Scientist — AI Controls and Monitoring As the leading data and evaluation partner for frontier AI companies, Scale plays an integral role in understanding the capabilities and safeguarding AI models and systems. Building on this expertise, Scale Labs has launched a new team focused on policy research, to bridge the gap between AI research and global policymakers to make informed, scientific decisions about AI risks and capabilities. Our research tackles the hardest problems in agent robustness, AI control protocols, and AI risk evaluations to help governments, industry, and the public understand and mitigate AI risk while maximizing AI adoption. This team collaborates broadly across industry, the public sector, and academia and regularly publishes our findings. We are actively seeking talented researchers to join us in shaping this vision. As a Research Scientist focused on AI Controls and Monitoring, you will design methods, systems, and experiments to ensure that advanced AI models and agents remain aligned with intended goals, even in high-stakes or adversarial environments. For example, you might: Develop monitoring techniques and observability methods that track AI behavior in real time to identify and flag deviations, emergent capabilities, or anomalous outputs; Research mechanisms for layered control, including fail-safes, oversight protocols, and intervention methods that can halt or redirect AI systems when risks are detected; Design red-team simulations to probe weaknesses in oversight and control mechanisms, and build mitigations to close identified gaps; Collaborate with policymakers, engineers, and other researchers to establish standards and benchmarks for AI monitoring and escalation. Ideally you’d have: Commitment to our mission of promoting safe, secure, and trustworthy AI deployments in the industry as frontier AI capabilities continue to advance. Practical experience conducting technical research collaboratively. You should be

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