Machine Learning Engineer Jobs

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. About the team Risk Detection is focused on providing a delightful experience for our merchants and minimizing friction, while ensuring the safety of our users in the financial ecosystem. Whenever the Risk team takes action on an account, we work to notify Merchants and provide clear status on what’s happening, enable guided workflows for resolving their issues, and redefine our overall Risk processes to make them as smooth as possible for good merchants. What you’ll do We’re looking for an engineering leader to lead and grow a strong team of engineers, build relationships with customers internally and externally, and champion our vision of making Stripe’s risk management a feature that attracts and retains merchants, and becomes a product differentiator. This is an exciting opportunity to partner with teams across Stripe to build the best merchant experience, and contribute directly to Stripe’s growth. Responsibilities Support the team in delivering a high level of technical quality and impact via APIs, user-facing experiences, services, and systems Recruit, hire, scale, and develop an amazing team of engineers Executing cross-functionally with leadership, product teams, infra teams & risk strategists Be actively involved in strategic direction and platform decisions that impact all of Stripe and Stripe customers 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

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. About the team Our Applied ML team aims to reform how our users interact with Stripe. We are doing so by (a) automating the easy tasks, and (b) assisting our users in the difficult tasks. Some examples include helping our users resolve issues with Stripe faster or making it easier for our users to sign up and navigate Stripe. We are using the latest LLMs as well as fine-tuning our own models. We're an end-to-end team going from ideas to models to shipping in production. You can learn more about our team’s work from this recent talk . What you’ll do As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. You will also have the opportunity to contribute to and influence ML architecture at Stripe as well as be a part of a larger ML community. Responsibilities Our team operates fluidly and here are some problems you may tackle: How do we evaluate a system offline & online? How do we improve performance to match (and beat) humans? How do we ensure model quality doesn’t degrade online? Does fine-tuning an LLM give us better performance? What are the right OSS and in-house platforms we should invest in? And in the process you will: 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 reliab

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. About the team Stripe Capital provides access to fast, flexible financing to small-and-medium businesses on Stripe to accelerate their growth, and we lent over $1B in 2024. Businesses use the funds for marketing, team growth, geographic expansion, working capital, new equipment purchases, and much more. Machine learning is core to Stripe Capital’s business—we use information about businesses from their activity within and outside of Stripe and our models to automatically underwrite uniquely tailored financing offers to their needs, which banks are often unable to do. We are doing so through models with an established performance history, data infrastructure that is Stripe scale, and a strong feedback loop that includes explainability, anomaly detection and a risk portfolio management layer. We're an end-to-end team going from ideas to models to shipping in production. What you’ll do As a machine learning engineer for Stripe Capital, you'll be responsible for designing, building, training, evaluating, deploying, and owning ML models in production with the goals of providing financing opportunities to as many users as possible while satisfying financial performance goals. You'll work closely with software engineers, data scientists, product managers, and risk managers to operate Stripe’s ML powered systems, features, and products. You'll also contribute to and influence ML architecture at Stripe and be a part of a larger ML community. Responsibilities Design

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. Make a Difference: Monitor and maintain deployed m

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Research Engineer, Distributed Data Systems, you will design and scale the infrastructure that powers large-scale multimodal training and evaluation at OpenAI. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI's rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable infrastructure in high-stakes environments. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security. Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. Partner with researchers to deeply understand requirements and translate them into production-ready systems. Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. You might thrive in this role if you: Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. Are detail-oriented and bring rigor to building and maintaining reliable systems. Demonstrate excellent software enginee

About the Team OpenAI’s API Multicloud team is responsible for extending OpenAI’s API platform into strategic cloud environments, starting with AWS . The team’s mission is to distribute OpenAI’s API broadly and safely by enabling key API technologies in AWS-native environments, in close partnership with Amazon and internal teams across Codex, Research, Safety Systems, and Applied. The team is focused on bringing core developer and enterprise capabilities into cloud-native environments, including AWS-hosted Codex, model customization / post-training as a service, and new stateful runtime environments for agentic workloads. This work sits at the intersection of production ML systems, developer platforms, model behavior, and large-scale infrastructure. About the Role We’re hiring Machine Learning Engineers to build and improve the AI systems that help strategic partners adapt OpenAI models to important use cases in cloud-native environments. This role spans post-training workflows, evaluation, data pipelines, model behavior, and API/infrastructure integration. You’ll work at the boundary between partner needs and core ML systems: helping teams understand what is and isn’t working, diagnosing issues in training and evaluation workflows, and turning those learnings into improvements to the underlying platform. You should enjoy working with external technical partners, extracting the real goal from messy requests, and pushing back or reframing when the requested experiment is not the highest-leverage path. You’ll collaborate closely with Research, Applied, Safety Systems, infrastructure teams, and external technical partners to solve ambiguous model-performance problems. When you succeed, strategic partners and internal teams will be able to improve model behavior with confidence, driving measurable product improvements while the systems behind that work become more reliable, scalable, and effective over time. In this role, you will Partner with strategic customers and in

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 hiring a Staff Machine Learning Engineer to help drive the future of merchant presence and shopping experiences on Pinterest. This role sits on the Merchant team and focuses on building AI/ML systems (including LLMs) that identify, understand, and surface relevant, high-quality merchants across segments—so Pinners can discover new brands with greater confidence and consideration, and merchants can reach new, diverse audiences. In this role, you’ll lead LLM-first, evaluation-driven initiatives—near-term focused on agentic workflows, measurement, and operational rigor that strengthen Merchant Integrity and Business Integrity. Longer term, you’ll help advance core relevance capabilities such as merchant/brand affinity modeling and related signals that improve shopping discovery across Pinterest. You’ll partner closely with Product Managers, E

About the Role: The Machine Learning team at Tubi drives the innovation behind personalized user experiences. With the largest inventory in the industry and hundreds of millions of viewers, we tackle problems in the space of recommendations, search, content understanding and ads optimization that shape the future of streaming. We are seeking a highly skilled Senior Machine Learning Engineer to contribute to transformative projects in video personalization. In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy. As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross-functional teams to develop and optimize machine learning-driven solutions. This is a hybrid role in our Toronto office. What You'll Do: Design, develop, and implement recommendation systems and algorithms for a global audience Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas Build and deploy high-impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high-quality user experiences. Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning-driven solutions that improve user engagement Your Background: 3+ years of industry experience building production Machine Learning systems BS, MSc, or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks Proficiency in building and deploying full-stack machine learning pipelines: data e

At Breeze, we're building the AI-powered infrastructure layer for global commerce, making it radically simpler for businesses to sell, get paid, and operate across markets. We go far beyond traditional payment processing. Breeze combines global payments, AI, stablecoins, and a Merchant of Record-like model to take on the complexity businesses typically manage themselves, including compliance, risk, fraud, chargebacks, reconciliation, and customer support. Our goal is simple: let businesses focus on building and selling great products while Breeze handles the complexity behind getting paid. Backed by Sequoia Capital , Multicoin Capital , and The Chainsmokers , Breeze is a successful, rapidly growing, and exceptionally well-capitalized company. We have the runway to think long term while remaining early enough that every person joining today can have a meaningful impact on what we build. We are hiring a Staff Machine Learning Engineer, Risk! As our Staff Machine Learning Engineer, Risk, you'll lead the evolution of our ML platform for payment risk, building the production-grade capabilities behind feature engineering, model training, deployment, monitoring, and continuous improvement. Risk decisions sit at the center of our business, and you'll own how those models get built, shipped, and kept healthy. This role reports to the CTO. You'll work closely with Risk, Software Engineering, and Data Engineering, and you'll be the senior technical voice for ML on the risk team. We're looking for someone who thrives in fast-moving environments, wants meaningful ownership, and is excited to build rather than simply maintain. What You'll Do Design and build ML infrastructure for payment risk detection, using Databricks as the core platform, in close partnership with software and data engineers. Bring structure to the team's ML environment: feature pipelines, versioning, job orchestration, and monitoring. Design and productionize models rather than just prototype them, including

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning. We hire Machine Learning Engineers across both our Consumer and Ads organizations, giving you the opportunity to work on a wide range of high-impact problems across the Reddit ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, — and who want to help shape the future of discovery, relevance, and monetization at Reddit. If you love working on complex, real-world ML problems at massive scale, this role is for you. What You’ll Work On As a Machine Learning Engineer at Reddit, you will design and build production ML systems that power core experiences across the platform, including: Personalized recommendations, search, and ranking systems that help users discover the most relevant content and communities Intelligent advertising systems including ranking, bidding, measurement, and optimization Content, Advertisers, and User understanding, from building foundational content/user representations to deriving insightful signals Large-scale machine learning pipelines, model serving infrastructure, and real-time decision systems Applied AI and

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview As a machine learning engineer in the Economics team, you will build state-of-the-art systems that blend rigorous economic thought with sophisticated machine learning algorithms to tackle some of the company's most challenging problems. Working in a horizontal team, you will have the opportunity to collaborate closely with partners across multiple functions to operate on a highly diverse set of problems, contributing both economic and engineering expertise in a fast-paced environment filled with exciting opportunities for technically-minded economists. The Economics team at Instacart works on a range of interesting and challenging problems across our platform, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team inclu

Who we are About the team Financial Connections is Stripe's open banking platform, enabling businesses to securely access consumer-permissioned financial data. Our platform connects to thousands of financial institutions, powering use cases from account verification to risk assessment to personal financial management. Across the Financial Connections Engineering org, we focus on delivering high-quality, enriched bank data at scale — building the ML systems that transform raw financial data into actionable signals for both internal Stripe teams and external merchants. Our ML work spans transaction categorization, risk scoring, data enrichment, and the development of intelligent systems that improve data quality across our network. We operate at the intersection of fintech infrastructure and applied machine learning, solving problems that directly impact Stripe's ability to serve millions of businesses and consumers. What you'll do We're looking for machine learning engineers who want to build intelligent systems that provide financial data at scale. You'll play a key role in designing, training, and deploying ML models that improve the quality, accuracy, and usefulness of financial data across Stripe's ecosystem. Responsibilities Design, build, train, evaluate, deploy, and own ML models in production that improve transaction categorization, risk scoring, and data enrichment across Financial Connections Design and build large-scale ML systems that operate on diverse financial data from thousands of institutions Experiment and iterate on ML models (using tools such as PyTorch, TensorFlow, XGBoost) 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 im

Senior Machine Learning Engineer — NY - New York. Apply via Workday.

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale. We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In

We're transforming the grocery industry At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers. Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table. Instacart is a Flex First team There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events. Learn more about our flexible approach to where we work. Overview The Digital Twin Platform team at Instacart is on a mission to understand exactly what is on store shelves at all times — bringing the precision and depth of a smart warehouse to every local grocery store across North America. Inventory estimates power some of the most critical products at Instacart, from search to logistics, and this team sits at the center of it all. Operating like a startup within a larger company, the team drives the end-to-end shelf data supply chain: ingesting data from retail partners, actively collecting novel inventory observations, developing sophisticated models, and integrating those outputs into live products at scale. We are looking for a Senior Machine Learning Engineer to help build the next generation of platforms for understanding, observing, and predicting inventory levels and in-store stocking dynamics in real time. In