Machine Learning Fellow Jobs

Who we are About the team The Radar ML team builds the fraud detection models that protect Stripe's $1.9 trillion payment network from fraud. The team owns 10+ real-time deep learning models that must constantly evolve to stay ahead of fraudsters. Each ML improvement translates directly into dollar impact for Stripe and its users. The team's models also power the Radar product suite that tens of thousands of businesses use to screen payments and manage fraud. Radar is growing fast, and the team is actively building new products like defenses against AI token theft, free trial abuse, and programmatic attacks. What you'll do In this role, you will own ML work across the full lifecycle: researching new fraud patterns, building and deploying models, and sharing results directly with top Stripe customers. You will have opportunities to optimize Stripe’s most intensive ML models, and opportunities to ship 0-to-1 products from scratch. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that detect fraud across Stripe’s global payments network Design and build large-scale ML systems that operate on diverse and large scale data Experiment and iterate on ML models to achieve key business goals around data quality and accuracy Develop pipelines and automated processes to train and evaluate models in offline and online environments Integrate ML models into production systems and ensure their scalability and reliability Collaborate with product, data science, and engineering partners across Stripe to identify opportunities where ML can improve outcomes for merchants and consumers Engage with the latest ML/AI developments and take calculated risks in transforming innovative ideas into productionized solutions Mentor engineers and contribute to a strong ML engineering culture within the team Who you are We're looking for someone who meets the minimum requirements to be considered for the role. If you meet these requirements, you are enco

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest is a visual discovery platform where hundreds of millions of people come to find inspiration and decide what to try, buy, or do next. Our Ads Quality organization builds the machine-learning systems that make ads relevant and valuable to Pinners while delivering meaningful outcomes for advertisers. We are seeking a Director of Machine Learning Engineering to lead a broad portfolio of Ads Quality modeling teams focused on engagement, conversion, ROAS optimization, ranking, representation learning, and ML-powered experimentation. In this role, you will shape and drive a unified technical strategy across Ads Quality, leading teams responsible for engagement ranking, oCPM and conversion modeling, ROAS optimization, lightweight ranking and retrieval models, foundation model adoption, sequence and multimodal modeling, and the quality and eff

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences– all created by our global community of developers and creators. At Roblox, we’re building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We’re on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you’ll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. ML Platform powers hundreds of use cases and billions of inferences per day across Discovery, Safety, Economy, and Creation. We build the primitives that let teams train, evaluate, deploy, and operate models quickly and safely—so a new ML idea can reach production in weeks or less. We’re looking for a Principal Platform Engineer who treats platform as a product : someone who can turn complex ML/AI infrastructure into clear, durable APIs, SDKs and easy-to-use CLIs/UIs that our internal developers love. This role blends product thinking, developer experience, backend engineering, and infrastructure at scale. Hands‑on ML experience is a plus; a track record of building internal platforms that developers love is a must. You Are Have 7+ years of professional experience and have a wealth of system design experience upon which to draw to build a scalable, reliable ML platform for all of Roblox. A Code Machine; you love not only to design and communicate ideas but also to actually ship product. You obsess about user feedback, and constantly drive towards getting platform features in customers hands. Proficient in API design and developer experience—gRPC/REST APIs, SDKs, CLIs, and simple UIs that de

We design Spotify's consumer experience—end to end, moment to moment, across every screen, platform, and partner integration. Our mission is to make listening feel effortless, personal, and joyful for billions of users around the world. That means turning complexity into clarity across hundreds of touchpoints—from our mobile and desktop apps to the smart speakers, TVs, cars, and integrations where Spotify shows up every day. If it touches a consumer, we shape it. We bring deep insight into human behavior, design, and technology to craft experiences that feel intuitive, expressive, and unmistakably Spotify. You'll lead a senior-heavy group of 10–12 machine learning engineers, including Staff engineers, who team up dynamically to solve high-priority business problems while staying deep in content understanding (audio, video and text). This is a player-coach role with a strong strategic remit: you'll shape where the group goes next, grow our audio understanding expertise over the long term, and help the team scale through thoughtful, practical use of AI in everyday engineering work. What You'll Do Lead, coach and grow a group of 10+ senior and Staff machine learning engineers who team up dynamically around business problems while staying deep in their domain. Set technical and team strategy for multiple content understanding problems and turn it into clear, achievable plans. Own delivery of high-priority company initiatives, from shaping the problem through to measurable impact for listeners. Stay close to the technology as a player-coach. Lead technical strategy, reviewing designs, guiding modelling and retrieval choices, and contributing hands-on where it helps the team most. Define and champion a practical point of view on how ML engineers use AI tools in their day-to-day work, and help the team realise real productivity gains. Partner with product, design, research and other engineering leaders across Spotify

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

Perplexity is seeking an experienced Machine Learning Engineer to advance how AI systems search, reason, and work together to solve complex problems. Our work spans search and retrieval, LLM post-training, multi-agent training, and the harnesses that make these systems effective. We control the full stack: the models, the agent harnesses, and the search infrastructure underneath. That gives us the freedom to develop new approaches across all three training models to use search more effectively, designing tools and execution environments around learned behavior, and improving retrieval to support how agents actually work. Responsibilities Push search and agent quality forward through improvements to models, training data, tools, and system design. Develop LLM post-training methods, including reinforcement learning, to improve reasoning, search, tool use, and task completion. Train and evaluate multi-agent systems, exploring how agents divide work, share information, and coordinate effectively. Design and build agent harnesses around the tools, context management, execution environments, and orchestration that support reliable work over many steps. Improve retrieval and ranking models and the search interfaces agents use to find and assess information. Build datasets, reward signals, and evaluations that expose meaningful failures and guide improvements. Own experiments end to end, from a clear hypothesis to scalable training, deployment, and measurable gains in quality, latency, and cost. Collaborate with AI, Search, Infrastructure, Data, and Product teams to bring new capabilities into production. Qualifications A strong track record of building and shipping ML systems, with deep experience in one or more of LLM post-training, reinforcement learning, search and retrieval, or agent systems. Strong software engineering skills and the ability to work across model training, experimentation infrastructure, and production systems. Experience designing rigorous evaluations

This is Adyen. Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H&M, and Microsoft - making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition. For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster. Financial Products About the Role The Financial Products org at Adyen is at the forefront of our evolution, building the foundational infrastructure that enables our customers to manage their finances, issue cards, and access credits and financing globally. Adyen is building a Machine Learning Engineering team in San Francisco focused on Credit Risk Modeling for Underwriting within Financial Products. This team will develop the models, scorecards, and production systems that enable Adyen to scale its credit products 100x. We’re looking for an enthusiastic, self-driven Engineering Manager to lead the Credit Risk Modeling team. You will lead the team that design, productionize, and operate machine learning models and rule-based decision systems that power credit products. Your team will work across the full model lifecycle, from research and data analysis to training, deployment, monitoring, and continuous improvement.. As an Engineering Manager, you will build, mentor, and coach a diverse and talented team of machine learning scientists and data engineers. You should be comfortable streamlining the team's engineering operations, refining product requirements together with product and merchants and encouraging effective collaboration. As a critical role in the continued success of our organization, you will help to itera

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

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 the Cohere TPM role? As our Generative Machine Learning organization has continued growing, we are looking for more Technical Program Managers to join the team! At Cohere, TPMs are pivotal to our success, being seen as operational experts specializing in cross-functional efforts. Great TPMs at Cohere are well-rounded, executing with precision at the tactical level, while partnering with senior leaders and shaping the big picture at a strategic level, and the opportunities are endless in growing the scale and impact of their work. Cohere’s TPMs would often be described as organized, execution-oriented, pragmatic leaders who are adaptable to the needs of the company and the programs they lead. As a reward for the depth and breadth of expertize that you bring to the table, you will get to work alongside some of the most talented AI researchers and industry experts in the world on building cutting edge AI technology. No day will be the same as the one before, and the dynamic high growth environment will be absolutely perfect for anyone excited about solving novel problems, bringing structure to oftentimes chaotic and fast-paced

We are hiring a Machine Learning Team Lead to lead a team of driven ML engineers working on translating cutting-edge research into ambitious, customer-centric speech solutions. As innovators in speech technology, our mission is to Understand Every Voice — a vision that has propelled us to be world leaders of Speech AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Machine Learning Team Lead to accelerate our efforts towards exceptional speech solutions. Our Modelling Team builds and trains a broad spectrum of models, including large self-supervised architectures, advancing Speechmatics’ mission to provide the most accurate speech recognition technology worldwide. It also ensures their deployment into production, working with the latest developments in ML, but also with the best practices for software engineering and model serving. What you’ll be doing: Lead, mentor, and grow a world-class team of ML engineers through coaching and professional development Provide technical oversight and guidance for end-to-end ML development, ensuring solutions are robust and scalable Guide the adoption of best practices in software engineering Plan work, allocate resources and collaborate cross-functionally to align initiatives with business objectives and bring solutions to production Drive the technical work for the ML team to deliver high-quality technical solutions that achieve ambitious strategic goals Who we are looking for: Demonstrable experience in guiding and mentoring ML engineers Adept at prioritizing work by impact, feasibility, and time-to-value, with clear success metrics Strong understanding of the modern Machine Learning stack, for example: - Knowledge of contemporary transformer architectures, related concepts (e.g., GQA , KV -caching) and best practices - Expertise in distributed training techniques - Familiarity with optimisation strategies for m

We are hiring a Machine Learning Team Lead to lead a team of driven ML engineers working on translating cutting-edge research into ambitious, customer-centric speech solutions. As innovators in speech technology, our mission is to Understand Every Voice — a vision that has propelled us to be world leaders of Speech AI. Fuelled by innovation, inclusivity, and a passion for making a global impact through world-leading Speech AI, we're looking for an experienced Machine Learning Team Lead to accelerate our efforts towards exceptional speech solutions. Our Modelling Team builds and trains a broad spectrum of models, including large self-supervised architectures, advancing Speechmatics’ mission to provide the most accurate speech recognition technology worldwide. It also ensures their deployment into production, working with the latest developments in ML, but also with the best practices for software engineering and model serving. What you’ll be doing: Lead, mentor, and grow a world-class team of ML engineers through coaching and professional development Provide technical oversight and guidance for end-to-end ML development, ensuring solutions are robust and scalable Guide the adoption of best practices in software engineering Plan work, allocate resources and collaborate cross-functionally to align initiatives with business objectives and bring solutions to production Drive the technical work for the ML team to deliver high-quality technical solutions that achieve ambitious strategic goals Who we are looking for: Demonstrable experience in guiding and mentoring ML engineers Adept at prioritizing work by impact, feasibility, and time-to-value, with clear success metrics Strong understanding of the modern Machine Learning stack, for example: - Knowledge of contemporary transformer architectures, related concepts (e.g., GQA , KV -caching) and best practices - Expertise in distributed training techniques - Familiarity with optimisation strategies for m

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . Pinterest helps Pinners discover and do what they love. The Content Foundation ML team is responsible for understanding the semantic meaning of Pinterest content and generating high-quality, reusable signals and insights that power relevance and personalization across the platform. We work at the intersection of machine learning, large multimodal models, data infrastructure, and product adoption to build foundational content understanding capabilities that support Discovery, Search, Growth, and Ads. We are looking for an experienced Engineering Manager who can drive the team’s technical direction, lead the team in building scalable content understanding systems, and make an impact on core Pinterest user and business outcomes. What will you be doing: Lead, mentor and grow a team of engineers and applied scientists in developing foundational conte

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . As a Machine Learning Intern at Pinterest, you’ll apply machine learning and AI to product and engineering challenges. You’ll work with engineering, product and data teams to prototype, evaluate and improve ML-powered features and discovery experiences. Throughout your internship, you’ll contribute to real projects, learn how large-scale ML systems are developed and build practical skills with guidance from experienced engineers. What you’ll do: Own a scoped machine learning project from problem definition through experimentation, implementation and communication of results, with guidance from your manager and team Contribute to applied machine learning and AI research that informs Pinterest product experiences Collect, analyze and synthesize data to develop data-driven machine learning models Write clean, efficient and maintainable code, suppor

About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here . We’re looking for a strategic and experienced engineering leader to define the technical direction for Pinterest’s advertiser measurement and signal-quality ecosystem. In this role, you’ll lead managers and senior technical leaders across Interfaces, Ingestion, User Match, and Conversion Quality, driving multi-year investments in machine learning, data platforms, experimentation, privacy, and production reliability. You’ll partner closely with Product, Data Science, Ads Quality, Infrastructure, Privacy, Legal and Sales to translate complex advertiser and business challenges into scalable solutions—and build an inclusive, high-performing organization equipped to deliver measurable impact at scale. What you’ll do: Define technical strategy and investment priorities across Interfaces, Ingestion, User Match, and Conversion Quality. Lead