Jobs in United States

Machine Learning Intern in United States

703 active opportunities · Updated October 2026

Explore current machine learning intern jobs across United States. Filter by work mode, employment type, experience, department, date posted and distance.

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📍 San Francisco, California, United States· Full-time
✓ High-confidence listingCompany trend -98.8%

From $154K/yr

Quick readStrong listing-quality and freshness signals

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: Airbnb’s mission is to create a world where people can Belong Anywhere. As we work to achieve that mission, we’re building world-class learning experiences for our technical teams. We’re looking for an exceptional and creative individual inspired to deliver innovative learning experiences that have tremendous organizational impact. The Difference You Will Make: The Staff Program Manager, Technical Education will play a key role in executing various technical learning programs including our Engineering Education programs that currently focus on AI Education, and other engineering and data education programming. Our focus is on impact and experimentation, creating world-class programs that enable technical excellence. We’re employing best practices from learning science and using measurement to iterate on learning experiences. The ideal candidate is confident in their ability to develop scalable learning experiences that drive overall growth and development for our technical audience. We are looking for someone who has the ability to synthesize a range of concepts into unified experiences, stay up to date in a rapidly shifting technical ecosystem, establish systems and processes, and deliver top notch program management. A Typical Day: Collaborate on and develop program strategy for various technical programs, including AI Enablement, AI Education, Machine Learning Education, Data Education, Engineering Education with internal SMEs and other Technical Learning & Development team members Design, create content, and project manage in-person and virtual technical learning

GitMachine LearningAIGo
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a

PythonAWSRestMachine Learning
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Role We are looking for a senior partner success and learning professional to activate cloud partners to co-sell and deploy customer solutions at scale. This role leads the enablement strategy and execution that equip partner teams to turn joint priorities into measurable customer and business outcomes. As a trusted advisor to strategic partners, you will turn shared business priorities into practical enablement programs that help partner sales, technical, customer success, and leadership teams identify joint opportunities, co-sell effectively, and deploy customer solutions successfully. You will own the partner enablement relationship for an assigned portfolio and work across internal teams to ensure programs are coordinated, scalable, and connected to measurable partner, customer, and business outcomes. This is not a traditional training delivery role or a quota-carrying partner account manager position. It is a consultative, partner-facing role for someone who can shape strategy, build relationships, translate complex AI capabilities into effective learning experiences, lead persuasive enablement sessions, and guide strategic partners toward sustained success. In this role, you will: Own strategic partner enablement and success Serve as the primary enablement and success lead for a portfolio of strategic cloud platforms. Develop a deep understanding of each partner’s business, priorities, audiences, existing learning infrastructure, and strategic relationship with our company. Build partner-specific enablement strategies aligned to shared goals, priorities, and the broader partnership strategy. Establish trusted relationships with partner leaders, alliance teams, enablement stakeholders, sales organizations, technical communities, and post-sales teams. Lead ongoing planning conversations, enablement reviews, stakeholder check-ins, and executive updates that keep partners and internal teams aligned. Identify gaps, risks, opportunities, and emerging partn

AWSRestMachine LearningAI
O
📍 Washington, District of Columbia, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the team The OpenAI for Government team partners with federal, state, local, defense, national security, and international public-sector organizations to securely and responsibly adopt frontier AI, strengthen public services, and deliver meaningful mission impact. About the role OpenAI is seeking a strategic and deeply technical leader to serve as the Head of Government Technical Success. This leader will oversee the technical functions across the government customer lifecycle, spanning pre-sales engagement, prototype-to-production delivery, and post-sales adoption and value realization. You will define and operate a unified technical success strategy across federal civilian, defense and national security, state and local, international public sector, and industry partners. Your mission is to help customers identify the highest value applications of OpenAI’s technology, navigate the technical and organizational requirements of government environments, move those applications into production, and scale adoption in ways that deliver measurable mission impact. This role combines organizational leadership, technical judgment, executive customer engagement, operating rigor, and product influence. You will partner closely with Government Sales, Product, Engineering, Research, Security, Legal, Global Affairs and Policy, and other teams to ensure a seamless customer experience for governments in the United States and around the world. This role is based in Washington, DC. We offer relocation support to new employees. In this role, you will Set and continuously refine the strategy, operating model, and priorities for Government Technical Success, aligning the organization to OpenAI’s broader objectives and the distinct needs of government customers. Build and lead an organization of technical success personnel, including hiring, organizational design, manager development, career growth, and high standards for technical and customer-facing excellence. Create a seamless

AWSRestMachine LearningAI
C
📍 New York New York United States, United States
✓ Quality checkedCompany trend +800%

Citi's Markets Quantitative Analysis (MQA) group is seeking a highly skilled VP Quantitative Analyst to join its Equities team. This role is central to the research, design, implementation, and maintenance of cutting-edge Equities Execution Algorithms for Citi's clients and internal trading desks, with a specific focus on North America and LATAM markets. This position offers a unique opportunity to apply strong quantitative, technical, and soft skills to foster innovation within a collaborative team culture, directly impacting trading businesses, control functions, and the global client base. Key Responsibilities Algorithmic Development & Enhancement: Design and develop new algorithms and strategies for the next generation equity trading platform initiative at Citi. Research, design, and implement improvements for existing algorithmic trading strategies (e.g., VWAP, liquidity seeking). Develop and enhance quantitative models, including optimal schedule, market impact models, and short-term predictive signals (e.g., fair value). Implement algorithm enhancements and customizations with production-quality code, applying best practices for modular, reusable, and robust trading components. Data Analysis & Modeling: Perform in-depth analysis of large datasets comprising market data, orders, executions, and derived analytics. Apply statistical modeling and machine learning techniques for data analysis and signal generation. Conduct flow analysis and performance tuning for various client flows. Provide data and analysis to support initial model validation and ongoing performance analysis. Collaboration & Support: Collaborate closely with traders, risk managers, product, sales, and technology teams to integrate quantita

PythonJavaMachine LearningArtificial Intelligence
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📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Observability team within the Infrastructure organization. As an early member of the Observability Team, you will be pivotal in building and shaping the observability experience for our internal and external customers. By joining this team, you’ll have a direct impact on the reliability and operational excellence of Basetens product systems. As Baseten scales its infrastructure across different cloud providers and diverse hardware, the volume and complexity of operational data is growing by orders of magnitude. This team is responsible for building high-throughput ingest pipelines, cost-efficient storage, and agentic diagnostic tools to ensure that we can detect, diagnose, and resolve issues in minutes rather than hours, even as the systems they operate become more complex. RESPONSIBILITIES Design and build scalable telemetry ingest and storage pipelines for metrics, logs, and traces across Baseten’s multi-cloud infrastructure Own and evolve core observability platforms, driving migrations and architectural improvements that improve reliability, reduce cost, and scale with organizational growth Build instrumentation libraries, SDKs, and integrations that make it easy for engineering teams to emit high-quality telemetry from their services Drive alerting and SLO infrastructure that enables teams to define, monitor, and respond to reliabi

PythonRestMachine LearningAI
S
📍 United States· Full-time
✓ Quality checkedCompany trend -87.9%

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 Fraud Strategy is responsible for building scaled fraud mitigation systems that prevent fraud and protect the financial ecosystem, while minimizing disruption to good users. The fraud team’s mission is to protect Stripe, our users, and the broader financial ecosystem from actors who abuse Stripe accounts for financial gain. What you’ll do As a Fraud Strategist, you will be responsible for building strategies to mitigate fraud (buyer fraud, seller fraud and account fraud) on new and existing Stripe products. You will enable safer money movement for our users and help Stripe manage fraud risks intelligently. The stakes are high, and you will be up against ever-evolving challenges. You will face some of the most complex and dynamic problems at the company, and the nature of your work will evolve rapidly to combat new and more sophisticated challenges to Stripe's integrity in the financial ecosystem. You'll partner closely with Product, Engineering, Data Science, Operations and other Risk Strategy functions to ensure fraud controls are embedded in every Stripe product. Beyond protecting against fraud risk, you'll drive innovation in how Stripe approaches fraud management— staying ahead of emerging fraud trends and pushing the boundaries of what effective, scalable fraud risk management looks like at a global payments company. Responsibilities Monitor portfolio to identify, mitigate and predict risky behavior that could result in loss

PythonSQLMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Forward Deployed Engineers work directly with the largest and fastest-growing AI companies in the world, owning their technical outcomes on Baseten and taking on the hardest problems in serving and improving models at scale. The work spans the model lifecycle: inference, post-training, and the systems that tighten the loop between them. Act as each account's de facto CTO on Baseten, with final accountability for how their workloads are designed, run, and scaled. Take customer objectives from vague to shipped: frame the problem, define the spec and success criteria, build the PoC, and carry it through to production quickly, using the right tools for the problem. Design the evals and benchmarks that isolate where quality or performance falls short, then close the gap yourself, whether that means optimizing inference, improving the model through post-training, or reworking the eval itself. Be the first responder to mission-critical failures including triage, owning the fix directly or route to the owning team and stay accountable until it ships. Build internal systems so that each engagement is faster than the last. This includes tooling and automation for eval and deployment infrastructure, and the recipes and reference implementations that make the product more self-serve. Shape the product itself, channeling what your accounts need into the roadmap and shipping fixes and features into Baseten's codebase yourse

KubernetesRestMachine LearningAI
B
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -79.1%

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE Baseten is seeking talented and experienced Software Engineers to join our Platform team within the Infrastructure organization. As a senior member of Baseten's Platform Team, you will own the systems that let every engineer at Baseten prove their code works before it reaches production. Our product runs mission-critical AI inference for customers who measure downtime in dollars per second, which means our internal bar for correctness, performance, and failure tolerance has to be exceptional. Your focus is the full testing stack: fast and reliable unit test tooling, integration harnesses that spin up realistic environments on demand, load and performance testing for GPU-backed inference workloads, and resilience testing that deliberately breaks things so our customers never have to find out what happens when a node dies mid-request. This is a builder role with org-wide leverage. You won't be writing tests for other teams — you'll be building the frameworks, harnesses, and feedback loops that make writing good tests the path of least resistance, and you'll set the standards for what "well-tested" means at Baseten. RESPONSIBILITIES Own Baseten's testing strategy end to end — define the standards, the tiers, and the tooling that engineering teams build against. Build and maintain unit, integration, load and performance testing frameworks Design end to end test infrastructure that provisions realistic dependencies

PythonDockerKubernetesCI/CD
R
📍 San Mateo, CA, United States· Full-time
✓ High-confidence listingCompany trend -100%

From $345K/yr

Quick readStrong listing-quality and freshness signals

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. Senior Engineering Manager, Safety Platform You will lead engineering pods within the Safety Platform organization, driving the technical vision and execution for the foundational systems that power every safety workflow at Roblox. You will own the core safety platform end-to-end: from the shared infrastructure and APIs that enable trust & safety capabilities across the company, to the tooling ecosystem that empowers internal operators to investigate, intervene, and resolve issues at scale. The scope also includes the Safety agentic platform — AI-powered systems that automate and augment safety workflows across detection, enforcement, and review pipelines. As the platform layer beneath every safety surface, your work will define how quickly and reliably Roblox can respond to emerging threats. This role requires a leader with a strong platform mindset who can balance technical rigor with broad organizational impact — working across User Safety, Trust & Safety Policy, Data Science, and Machine Learning to deliver scalable, extensible, and high-availability systems for one of the world's largest platforms. You Will: Lead and Develop: Recruit, hire, mentor, and inspire a diverse team of

AWSGitMachine LearningAI
R
📍 San Mateo, CA, United States· Full-time
✓ High-confidence listingCompany trend -100%

From $295.3K/yr

Quick readStrong listing-quality and freshness signals

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 @ Roblox today supports hundreds of ML use cases and billions of inferences per day across Discovery, Safety, Engine, and much more. As a Model Optimization engineer on ML Platform, you will be responsible for digging deep into model internals to optimize performance, for both training and inference. We are looking for accomplished engineers to help us maximize performance of our platform. You Will: Optimize machine learning models for performance on GPU architectures, focusing on both training and inference workflows. Conduct low-level performance profiling analysis to identify bottlenecks in existing machine learning pipelines and propose actionable improvements. Contribute to the development of best practices and tooling for model optimization and deployment. Collaborate with cross-functional teams, including data scientists and software engineers, to integrate and deploy optimized models into production environments. Partner across organizations to build tooling, interfaces, and visualizations that make the ML@Roblox a delight to use. You Have: 6+ years of professional experience and a tool chest of system design experience upon which to draw to build performant system

AWSGitMachine LearningAI
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📍 United States· Full-time· Remote
✓ High-confidence listingCompany trend -85.6%

From $163.6K/yr

Quick readStrong listing-quality and freshness signals

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 . The Ads & Monetization organization sits at the heart of Pinterest’s business, where machine learning, AI, creatives, attribution, reach, and marketplace come together to create value for advertisers and relevant, inspiring experiences for Pinners. Pinterest is at an inflection point. Hundreds of millions of users come to the platform with active commercial intent — making Pinterest uniquely positioned to influence the full purchase journey from inspiration to action. We are building a path of non-linear growth with emerging surfaces, expanding international markets, and foundational investments in relevance, advertiser return on ads spend, measurement, and creative quality. Unlocking that path requires disciplined, technically sophisticated execution across a collaborative, multi-team environment spanning technology, strategy, go-to-

AWSRestMachine LearningAI
A
📍 San Francisco, United States· Full-time
✓ High-confidence listingCompany trend -98.8%

From $168K/yr

Quick readStrong listing-quality and freshness signals

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. The Community You Will Join: The Total Rewards Compensation team serves as a strategic advisor to business leaders, managers, and employees across Airbnb. We are compensation experts with a deep understanding of our stakeholders, problem solvers who use data and insights to drive value, and partners who build the tools, models, and frameworks that support sound compensation decision-making across the company. This role sits within the Compensation function and will work closely with the Technology organization and cross-functional partners including Recruiting, People Analytics, Finance, Legal and Talent. The Difference You Will Make: We are looking for a Technical Compensation Partner to serve as the dedicated compensation partner for the Technology organization, covering Engineering, Infrastructure, Machine Learning, and Data Science. This role will support VP and Director level tech leaders and their Talent Partners as the primary day-to-day compensation resource. The ideal candidate will be a strong business partner and a builder of compensation programs, tools, and data infrastructure, and must be comfortable operating with autonomy in a fast-moving environment. A Typical Day: Serve as the dedicated compensation partner for the Technology organization, supporting VP and Director level leaders, Talent Directors, and People Partners across Engineering, Infrastructure, ML/AI, and Data Science. Act as the primary point of contact for Talent Directors and senior tech leaders on new hire offers, internal equity reviews, leveling decisions, and out-of-cycle requests. Own compensation cycle execution f

PythonSQLMachine LearningAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We are looking for an experienced Research Engineer to work on retrieval & search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval & search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. You will be at the center of our retrieval & search efforts as a company, and the progress you drive here will reach millions of end users. In this role, you will: Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search. Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users. Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term. Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world You might thrive in this role if you: Have extensive prior experience building and maintaining production machine learning systems. Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases Have prior experience building and iterating on internet-scale search systems Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or de

AWSRestMachine LearningAI
O
📍 San Francisco, California, United States· Full-time
✓ Quality checkedCompany trend -80.2%

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructu

AWSKubernetesRestMachine Learning
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