Research Science Intern in Canada

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

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

Are you a self-starter who loves tackling challenging problems in a team-oriented, fast-paced environment? Do you love the idea of living in Vancouver? Our quantitative equity team is expanding, and we are looking for talented individuals whose skills and interests are aligned with the team’s mission to deliver superior investment performance to our clients through a disciplined, systematic investment approach. Jobs within our team lie at the exciting intersection of research, data science, finance, and technology. A culture of innovation, career growth and success through collaboration has enabled us to deliver superior investment performance to our clients for over two decades. Today, our clients entrust us with over $78+ billion USD in financial assets. What You Will Do This is an exciting opportunity for individuals who are passionate about learning the quantitative equity investment management business and excited to tackle a broad range of investment, mathematical, and technology challenges. You will start with a comprehensive training program, learning about various elements of quantitative equity investment management. You will then continue to a specialized group within our team based on a combination of your fit and preference. Your specialized role may involve building, scaling, managing, monitoring, and/or trading our quantitative model and portfolios. You will be supported with coaching and mentorship from senior members of the team. We are creating the conditions for you to grow your career steadily over time. Groups within our team where you can contribute and gain valuable experience include: Investment Process Management Our Investment Process Management (IPM) group plays a central role in building highly scalable, efficient, and robust process management systems. The processes and infrastructure we maintain are critical in the team’s ability to d

Join us in building the future of finance. Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading. About the team + role We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. The Crypto Data Science team is on a mission to accelerate Robinhood's position as the leading platform for crypto investors. We partner with product, engineering, finance, and research to shape the strategies behind our fastest-growing business. From launching new products to expanding internationally, our team turns complex data into clear decisions — and our work directly influences how millions of customers experience crypto at Robinhood. As the Data Science Manager for the Crypto team, you will lead a high-impact team delivering insights, models, and strategies that shape Robinhood's crypto product roadmap and growth. This role partners with product, engineering, and executive leadership to ensure data is at the core of our strategic decisions. Learn more about what the crypto team is up to here . This role is based in our Menlo Park, CA office, with in-person attendance expected at least 5 days per week. At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. What you’ll do Lead, mentor, and sca

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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. Data Science is at the heart of Lyft’s products and decision-making. Data Scientists at Lyft operate in dynamic environments, moving quickly to build the world’s best transportation solutions. We tackle a wide range of challenges - from shaping long-term business strategy with data, to making critical short-term decisions, to developing algorithms and models that power both internal systems and customer-facing products. Driver Incentives Science owns the algorithms and systems behind incentive design, influencing driver engagement and marketplace efficiency — from real-time supply positioning to longer-horizon earnings and engagement programs. The team is responsible for designing pay and incentive mechanisms that are efficient and good for driver experience over the long run. As a Data Scientist specializing in Algorithms, you'll partner closely with product, engineering, and operations leaders to build and scale incentive systems, shape long-term mechanism design strategy, and deliver on critical business goals tied to marketplace efficiency and driver earnings. Candidates with strong optimization backgrounds — think mathematical programming, control theory, or operations research — are a great fit, though we welcome strong candidates from machine learning or causal inference as well. The ideal candidate thrives in a fast-paced environment and brings a hands-on, entrepreneurial mindset to drive results. Responsibilities: Collaborate with engineering and product teams to design, implement, and iterate on new features and algorithmic improvements for driver incentives and pay mechanisms. Design, develop, and deploy optimization models, algorithms, and systems for problems such as budget allocation, multidimensional cost-curve development, and incentive targeting. Write production model code; collabor

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 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

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

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

The Opportunity This is a critical and exciting time at Enigma. Our customers consistently tell us that our data products create tremendous value and are deeply aligned with their most important workflows. As demand grows, we have an urgent opportunity to improve both the intelligence of our data and the systems through which customers access it. We are looking for an experienced Senior/Staff Machine Learning Engineer to join our Match Team and help shape the next generation of Enigma’s customer-facing data products. In this role, you will combine advanced statistical and machine learning research with the engineering systems required to power fast, relevant, and reliable search experiences at scale. This is a uniquely high-impact role sitting at the intersection of information retrieval, ranking systems, semantic search, distributed systems, and customer data delivery. The Role At the core of Enigma’s product is our data, which makes both data science and delivery systems central to what we build. As a Senior/Staff ML Engineer on the Match Team, you will lead efforts that improve the relevance, latency, and scalability of our customer-facing data products. You’ll work across the full lifecycle: framing retrieval and ranking problems, developing models and experimentation strategies, evaluating results using real-world signals, and implementing high-throughput search and retrieval systems. This role is ideal for someone who is excited by both hard ranking/search problems and the systems challenges of turning those solutions into low-latency, production-grade retrieval systems. What You'll Do Develop innovative solutions to complex problems in information retrieval, ranking, semantic search, query understanding, and recommendation systems Build and optimize low-latency, high-throughput search APIs, indexing pipelines, and retrieval systems using Python, Typesense, and AWS Evaluate and evolve our search technology stack, driving technical design decisions across index

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 connects people to transportation to change the way we live and get around our communities. We are looking for product managers who bring exceptional creative and analytical skills to drive forward a best in class product. Product management at Lyft leads the integration of engineering, data science, and design to achieve the company’s vision for reinventing transportation. We are looking for entrepreneurial and passionate Product Managers to innovate and execute across a rapidly growing, fast paced company and industry from our San Francisco headquarters. The Core Rider team is responsible for the Lyft consumer app you know and love. This team spans the entire consumer journey across the request and purchase flows, search, pickups and dropoffs, the post-match experience, and the in-trip experience. As a Staff Product Manager on the Core Rider team, you’ll lead a large cross-functional team to build the rider “journey” (anything that gets a rider from A to B.) This includes the home screen, request flow, pickup experience, in-ride experience, and rate & pay. You’ll also be responsible for how this “golden path” experience extends to serve AVs and segments of interest – owning targeted experiences like Lyft Silver for Seniors and Price Lock for commuters. This represents a large percentage of the core Lyft rider experience used by millions of people every day. Plus, the solutions you build need to work everywhere, from the simplest suburban home to JFK Airport, and all modes of transportation (rideshare, AVs, etc.). Responsibilities: Understand Lyft's strategic and competitive position. Set goals and success metrics that align with Lyft's mission and drive maximum impact based on data analysis, market research and usability studies Set an incredibly ambitious vision that motivates and i

Airtable is the no-code app platform that empowers people closest to the work to accelerate their most critical business processes. More than 500,000 organizations, including 80% of the Fortune 100, rely on Airtable to transform how work gets done. Airtable’s mission is to bring the power of computing and software development to everyone. We are developing a powerful and extensible toolkit that our customers can leverage to solve a variety of different problems and workflows. We’ve seen our most sophisticated customers use the product to run global processes across thousands of employees, coordinate precision manufacturing pipelines, and consolidate previously siloed mission-critical data into a single source of truth. The complexity of these use cases requires us to be extremely thoughtful about how we design and implement new functionality in the product and make sure it’s both easy to use and comprehend for our customers and maintainable for us. As a Full-Stack, Backend engineer at Airtable, you will have the opportunity to work with customers to deeply understand their needs and workflows. You will collaborate with cross-functional partners across product management, design, research and data science to create innovative new features that enable our customers to do their best work. You will be responsible for owning and executing the end-to-end implementation of these new features that will contribute to making our toolkit even more powerful and successful. We currently have openings on: The Admin & Governance Team (Full-Stack/BE) ensures Airtable is secure, compliant, and enterprise-ready. It owns key admin capabilities like the Admin Panel, SSO, and audit systems, as well as foundational features like User Groups. This team's mission is to accelerate organizational value for the largest customers with enterprise-first governance and controls. The Omni Capability & Quality Team (Full-Stack/BE) brings the power of AI directly to Airtable end users—

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

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