Systems Research Engineer Intern Jobs

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based New York City. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurab

About the team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in Seattle. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and measurable

About the Team OpenAI’s Forward Deployed Engineering team partners with healthcare organizations to deploy production AI systems across clinical, operational, and member-facing workflows. We work at the boundary of customer deployment and core platform development, using customer engagements to define repeatable architectures, evaluations, integrations, and operating standards for complex, regulated healthcare environments. About the Role We are hiring a Forward Deployed Engineer (FDE) to own end-to-end deployments of our models within healthcare organizations, including payers, providers, health systems, and healthcare technology companies. You will lead technical discovery, architecture, implementation, evaluation, productionization, and handoff, translating complex customer workflows, data, infrastructure, and regulatory constraints into production AI systems. You will measure success through production adoption, measurable workflow impact, and evaluation loops that establish customer-specific benchmarks, acceptance criteria, and launch readiness. You’ll collaborate directly with customer technical and operational teams, alongside internal Business, Research, Product, Engineering, and Security partners, to deliver solutions and translate deployment learnings into product improvements. This role owns the technical solution; ownership of the commercial or executive relationship is not required. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Own the technical solution end to end, from customer discovery and workflow scoping through architecture, hands-on implementation, evaluation, production deployment, adoption, and handoff. Partner credibly with customer engineers, operators, and domain experts to frame ambiguous problems, define scope, and translate payer, provider, or health-system workflows into technical requirements and mea

About the Team We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. About the Role We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most p

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the Role We're looking for a Software Engineer to join the team building Claude Security. In this role, you'll take new security capabilities in frontier models and turn them into products that customers can rely on, working across the full stack from early prototype through production. This role sits close to both research and go-to-market. You'll work with researchers on the team to understand what the models can do and where they fall short, and with customers and partners to understand which problems are worth solving for them. You'll be expected to form your own view from both and to own significant pieces of the roadmap, including deciding what not to pursue. The right candidate is a strong generalist engineer with the technical depth to engage with research, the product instincts to know what's worth building, and the drive to move fast. Prior security experience is useful but not required; range across the stack and good judgment about what to build matter more. Responsibilities Build and ship user-facing and/or backend features for Claude Security Build the agent loops, tool integrations, and enabling infrastructure for cybersecurity products Collaborate tightly with product managers and go-to-market to understand user needs, shape feature scope, and make informed tradeoffs as you build Iterate quickly based on user feedback and internal testing, improving the experience on a continuous basis Collaborate with research teams to identify and develop new model capabilities for security applications You may be a good fit if you: Contribute across the stack, from front-end UI to back-end infrastructure Are proficient in Type

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation. You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives. This role is exclusively based across our San Francisco & Seattles sites. We offer relocation assistance to new employees. In this role, you will: Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems Architect large-scale distributed systems that

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role At Anthropic, we're building AI systems that are safe, beneficial, and transformative. Our mission is to develop AI that benefits humanity, and we believe the most powerful capabilities emerge when we thoughtfully bridge the gap between research breakthroughs and real-world applications. Anthropic Labs serves as our internal accelerator. We're looking for the next breakout hits that bring substantial revenue or transform an industry. We operate in close partnership with research and build through fast iteration cycles. Past successes include Claude Code and MCP. We're seeking versatile, entrepreneurial engineers to join Labs. In this role, you'll work at the intersection of cutting-edge research and real-world application, rapidly building and testing new experiences, working directly with researchers and users, and generating the insights that shape Anthropic's product future. You'll need to be comfortable with ambiguity, willing to kill your own projects when the data says to, and energized by the pace of building in uncharted territory. Responsibilities Rapidly prototype full-stack applications that showcase emerging AI capabilities, shipping early and often to maximize learning Collaborate closely with research teams to understand new model capabilities and translate them into intuitive user experiences Work directly with internal test users and external partners to gather feedback, iterate quickly, and validate (or invalidate) product concepts Design and run structured experiments to test hypotheses, balancing creative exploration with rigorous evaluation Generate documentation and insights to guide successful prot

P-78 At Databricks, we are passionate about enabling data teams to solve the world’s toughest problems, from advancing AI research to powering next-generation applications. We do this by building and operating the world’s best data and AI infrastructure platform. Founded by engineers and driven by customer obsession, we embrace the hardest technical challenges, whether it’s scaling distributed systems across multiple clouds or delivering reliable, low-latency communication between thousands of services. And we’re only getting started. As a Senior Software Engineer on the Application Traffic team , you will design and build the systems that power Databricks’ service-to-service communication across thousands of clusters in a multi-cloud environment. You will also help create abstractions that hide networking complexity from product teams, making connectivity, discovery, and reliability seamless by default. The impact you’ll have: You’ll work across three key areas that define Databricks’ networking stack: Ingress Control Plane : Build the control plane for Databricks’ global ingress layer. Enable programming of API gateways with static and dynamic endpoints, simplify service onboarding, and make it easy to expose APIs securely across clouds. Service-to-Service Communication : Design scalable mechanisms for service discovery and load balancing across thousands of clusters. Provide networking abstractions so product teams don’t need to worry about underlying connectivity details. Overload Protection : Build intelligent rate limiting and admission control systems to protect critical services under high load. Ensure reliability and predictable performance for both customer-facing and internal workloads. What we look for: BS (or higher) in Computer Science or related field 5+ years of experience designing and building large-scale distributed systems Strong proficiency in one or more languages such as Java, Scala, Go, or C++ Experience with service-oriented architectures an

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

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

Position Overview Our customers are at the forefront of some of the most interesting data in the world, using SingleStore to push the boundaries every day. To do this well, they leverage the expertise of our Support Engineering Team, composed of technical subject matter experts on the frontline of critical customer issues. This Support Engineering role skews far more towards engineering than typical technical support as you will need to delve into database internals and memory allocators, investigate Linux and host-related configurations, and diagnose SQL query behaviour, all in the name of resolving complex database issues. Our Support Engineers are constantly learning a wide range of customer systems and technical concepts and are thrilled by the new and exciting challenges that they encounter on a regular basis. To accurately identify the source and solution of an issue, this team will take the time to learn about the customer’s business and systems while helping to improve their fundamental SingleStore and database operational knowledge. This often requires additional research and time spent on learning new technologies and tools outside of SingleStore while also being deeply engaged with multiple departments including development teams, query performance engineering, product management, infrastructure SREs, etc. Required Hours The hours required are from 11:30 AM IST - 8:30 PM IST (9 hours) for 5 days Participate in our on-call rotation that may include weekends and holidays. Role and Responsibilities Provide email and live technical support to our enterprise customers, acting as the first line of defense for complex technical issues, bug diagnosis, or resolving critical outages. Identify and reproduce product issues, perform QA, and submit formal bug reports or feature requests to the appropriate Engineering team. Collaborate closely with software developers, sales engineers, and technical account managers to keep all teams up to date with current

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Anthropic Anthropic's mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most. About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments, Life Sciences team. Our goal is for Claude to close the loop on scientific discovery, and a significant part of this is helping Claude to drive scientific hardware and software. You'll help deploy the Model Hardware Standard (MHS) to labs doing the world’s most important research. You’ll scale what you learn in the field by contributing back to the standard, building scalable assets, and driving associated internal product and research direction. Responsibilities Work with labs to automate their experiments end-to-end with Claude - from advising, to prototyping, to writing production code. Drive product, engineering and research direction based on field experience - e.g. building evals to measure limitations of our models in the physical world (capabilities and safety), developing new features on MHS, etc. Scale your impact to the long tail of labs through reusable cookbooks,

About Snorkel Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine technology with research-driven AI data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded out of the Stanford AI Lab in 2019, Snorkel works with leading AI labs and enterprises to move from better data to better outcomes. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! The Role As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This will involve designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of Snorkel’s tooling. Develop and implement state of the art AI systems such as retrieval-aug

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the team Secure Frameworks is the team in Anthropic's Security Engineering org that builds shared security libraries and frameworks the rest of the company builds on. We collaborate closely with teams and leaders across Anthropic to own critical security foundations, including workload identity and authorization, cryptographic frameworks, and the centralized access proxy that secures traffic to internal applications. Our mission is to make the secure thing easy and the easy thing secure by helping Anthropic engineers get secure behaviour by default and preventing entire classes of vulnerabilities through careful design. We own what we ship, help customers adopt better security practices and at times we work embedded directly in research, infrastructure or product teams. About the role You will design, build and run security foundations used across Anthropic's fleet, from threat model through production, on-call and adoption. Much of the work is greenfield: our infrastructure is growing quickly and the timelines are compressed, so you will help define the architecture rather than inherit it. Depending on your strengths you will focus on one or two of the areas below and contribute across the rest. Build critical security foundations including cryptographic frameworks, mTLS infrastructure, secure serialization, and authorization systems, designed to prevent entire classes of vulnerabilities Partner with product, research, infrastructure, and other security teams to ensure frameworks integrate smoothly with lower-layer security controls Scope, design and build security services and libraries end-to-end, maintain t

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role Anthropic's Legal Tech engineers play a specialized and critical role in keeping Claude at the frontier. Partnering closely with counsel, we provide custom infrastructure and guidance for complex, novel technical matters, empowering teams across the company to continue meeting our legal obligations as we innovate. As a Senior+ Software Engineer on our Legal Tech team, you'll build dedicated, highly secure, and reliable cloud environments and data processing and storage capabilities at speed and scale. You will own your scope end to end: from raw requirements all the way through to large-scale production systems that satisfy legal invariants and unlock new possibilities. The systems you build won't just be dependable and scalable; they'll be interpretable and auditable, demonstrating to skeptical audiences exactly how they worked and why results can be trusted. You'll be an essential member of a collaborative team, working together to solve difficult problems against fixed deadlines. You will own internal customer relationships as well: you'll gather, prioritize, and coordinate needs from colleagues on Privacy, Security, Research, and/or Infra as well as Legal, to ship the right capabilities on the right timelines. You'll act as a trusted advisor: clearly explaining technical concepts and constraints to inform legal decisions, and proactively designing new approaches to prevent classes of problems. Your infrastructure expertise will directly empower our business to calibrate and manage risk, innovating faster thanks to systems that build in legal considerations. Key responsibilities Build and operate dedicated cloud infr