Product Design Intern in United States

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. 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’re building the observability product for OpenAI—from scalable infrastructure to a rich, AI-powered UI. Our systems ingest over petabytes of logs and billions of time series metrics across our fleet. We're now layering intelligence on top—think agents that summarize SEVs, auto-generate dashboards, or help engineers debug through notebook-like UIs. We’re hiring software engineers across the stack—infra, backend, and product. You’ll join a small, gritty team building both foundational infra and novel internal tools to make OpenAI's production systems reliable, performant, and observable. What You’ll Do Own core observability infrastructure, including distributed logging, time series, and trace storage Build AI-native tools that help engineers detect, understand, and resolve issues autonomously. Contribute to UI experiences like dashboards, notebooking, or interactive debugging Collaborate closely with engineers, researchers, user ops, and other teams across the company to build the next generation observability product You Might Be a Fit If You: Have operated large-scale distributed systems in production. ( especially logging systems or some other time series databases) Thrive in ambiguous environments and roll up your sleeves to solve unscoped problems. Have full-stack chops or product sensibilities—you're excited to build real tools people use. Have strong fundamentals in systems, networking, and cloud infra (Kubernetes, AWS, etc). Bonus : built or contributed to observability systems (e.g. Prometheus, OpenTelemetry, etc). Why This Team We’re b

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

About the Role The Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production. We own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration. In This Role, You Will Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions. Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback. Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows. Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale. Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns. Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks. Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling. Technologies commonly used in this environment include: Kubernetes for large-scale container orchestration and runtime infrastructure Python and FastAPI for internal services Terraform for infrastructure as code GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems) Buildkite for CI orchestration You may be a strong fit if you: Have worked with Kubernetes-based deployment systems at scale Have experience building or operating continuous deployment platforms Are familiar with GitOps tooling such as

Embedded Firmware and Software Engineer Description - This role is responsible for driving design, development, and debugging of embedded software/firmware for hardware, ensuring efficient and reliable operation. The role collaborates with hardware engineers to integrate software and firmware with hardware components, ensuring seamless communication and functionality. The role works closely with software developers, hardware engineers, quality assurance, and product managers to deliver high-quality products. Responsibilities Owns the preparation and creation of instructional technical manuscripts for firmware operation. Allocates resources to complete programming projects, and designing detailed plans to ensure firmware is functioning properly. Designs enhancements, updates, and programming changes for portions and subsystems of firmware, including DSP, embedded code, EFI drivers, EFI applications and BIOS/UEFI. Analyzes design and determines coding, programming, and integration activities required based on general objectives and knowledge of overall architecture of product or solution. Writes and executes complete testing plans, protocols, and documentation for assigned portion of application; creates solutions for issues with code and integrates into application architecture. Leads a project team of other software firmware engineers and internal and outsourced development partners to develop reliable, cost effective and high quality solutions for assigned systems portion or subsystem. Collaborates and communicates with management, internal, and outsourced development partners regarding firmware design status, project progress, and issue resolution. Represents the software firmware engineering team for all phases of larger and more-complex development projects, from microarchitecture design thro

Senior Designer Description - ABOUT THE ROLE We’re looking for a Senior Designer who leads by doing. This is an equal-parts strategic and hands-on role — someone who sets the creative bar for our in-house agency, earns credibility through exceptional work, and isn’t afraid to roll up their sleeves when it matters. You champion design excellence, can defend your decisions with clarity and confidence, and help grow the people around you. This role sits within a balanced creative environment: you’ll have real influence over the work, while partnering closely with internal clients across marketing, sales, and product who hold final approval. Success here means earning trust through quality and communication, not just creative instinct. Day-to-day you’ll operate across mid-to-lower funnel channels — social, ecommerce, retail, sales enablement, and short-form video. You think like a creative director but know that craft lives in execution. Production is where the rubber meets the road, and you’re proud to be there. WHAT YOU’LL DO Produce exemplary design work across social, etail, retail, sales decks, and short-form video that raises the quality bar for the whole team Partner with internal clients across marketing, sales, and product — translating briefs into design that performs and building lasting working relationships Concept and execute with both visuals and words — thinking across design and messaging together, not in isolation Defend design decisions with strategic rationale, balancing business goals with creative integrity Contribute upstream — shaping briefs, influencing strategy, and catching creative problems before execution begins Maintain and evolve brand standards, ensuring visual consistency across all channels and touchpoints Build scalable systems — templates, as

Replit is the agentic software creation platform that enables anyone to build applications using natural language. With millions of users worldwide, Replit is democratizing software development by removing traditional barriers to application creation. About the Team Product Platform builds and owns the shared foundations the rest of Replit is built on, spanning the full stack so every other team can ship features safely and quickly. Identity & Authorization defines how people, agents, sandboxes, and services prove who they are and what they can do. These systems protect critical product and service interactions across Replit's web product, Agent, enterprise controls, and internal services. Our work is high-leverage and horizontal: when identity and policy are clear, reliable, and easy to adopt, every other team can move faster without rebuilding security controls. We are a small, collaborative team that values curiosity and clear thinking over pedigree, and we work in the open by bringing each other the problem rather than just the request. We care more about how you reason and build than the route you took to get here. About the Role As a Software Engineer , you will design, build, and operate the identity and authorization systems that protect critical interactions on Replit, including Agent acting on behalf of a user or holding their own identity. The work is guided by a few simple questions: Can every protected request prove which workload made it, which principal it represents, and who is acting on that principal's behalf? Can product teams express policy once and trust the same decision across web, mobile, Agent, and internal services? Can enterprise administrators control who can access each workspace, app, connector, and Agent capability without navigating a permission maze as well as having a legible ledger of decisions? Can Agent act for a user across long-running and durable work without receiving broad or long-lived credentials? Are identity and auth

NVIDIA is looking for an experienced software engineer with infrastructure experience to become a senior member of the Cloud Foundations Automation - Development Team. We build and manage the automation ecosystem supporting NVIDIA's GPU Cloud and NVIDIA SuperPod deployments. NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most hard-working and dedicated people on the planet working for us. If you're creative and autonomous, we want to hear from you! What you'll be doing: Developing software to enable efficient network design, deployment and day 2 management. Building product focused software solutions, used by internal and external customers. Helping us as we transform our workflows and organization into a centrally orchestrated configuration management framework, operating at scale across geographies. Owning and driving integrations with various service APIs such as Cloud Service Providers, to automate creation of environments and auto populate data sources in turn. Building on open source software, designing and implementing data structures and UI interfaces to automate processes from equipment purchase to device config generation to deployment to operations. Streamlining deployment mechanisms and life cycle operations Developing modern service architectures around streaming data and event pipelines. Working with infrastructure domain experts on true, zero touch deployment solutions and utilizing best of breed high performance computing management solutions. Be a proactive problem solver, looking out for new opportunities to improve our services and customer experience. Communicate readily with your peers across the organization, b

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

Work Flexibility: Onsite Stryker is seeking a Staff Advanced Manufacturing, Automation/Software Engineer to join our Advanced Operations team, supporting the Medical Division - Acute Care Business Unit. In this role, you will lead the design, development, and deployment of advanced automation and production test systems for new product introductions. This role is critical to ensuring reliable, scalable, and compliant manufacturing for patient support and patient environment products. You will serve as both a technical owner and a supplier-facing leader, architecting systems internally while guiding external partners to deliver high‑quality automation solutions. You will have the opportunity to work on the design transfer of new products from research through development and into production. This is a hybrid role based out of Portage, MI. The team works onsite 4-5 days per week to support collaboration and project needs. What you will do: Automation System Architecture & Development Lead the full lifecycle of industrial automation and test systems from requirements, architecture, and design through implementation, validation, and release. Define system-level requirements encompassing mechanical, electrical, software, controls, and safety considerations. Develop and integrate control software, embedded interfaces, test sequences, and operator interfaces (HMI/SCADA). Ensure robust performance, maintainability, reliability, and alignment with design intent and manufacturing needs. Troubleshoot complex processes, software, and equipment issues; optimize system performance and uptime. Supplier & Equipment Vendor Leadership Manage automation and equipment suppliers, including capability assessments, technical reviews, process monitoring, and on‑site visits. Create clear, comprehensive

About the Team The Human Data team turns human feedback into reliable signals for training and evaluation. We design and run end-to-end programs that capture the depth of human intent behind everyday and high-stakes uses of our models. Our remit spans bespoke data campaigns, scalable synthetic data generation, and product-embedded signals. We partner closely across all research teams to translate these signals into training datasets, novel evaluations, and feedback loops that push the frontier of our models and advance their applications. About the Role As a Program Manager (PGM) in the Human Data team you will partner with our research teams, operations and engineering to execute complex programs for collecting high-quality data. You will be a key interface between our external vendors and AI trainers, ensuring human data campaigns are successfully completed. Your work will play a key role in enabling OpenAI to train safe models that will land in the real world This role is based in our San Francisco HQ. In this role, you will: Work in a high velocity environment, where the outcome of your work will have a direct impact on the models that OpenAI deploy in the real world Work closely with external vendors, trainers and internal researchers to collect, review, and deliver high-quality data Gather requirements, write instructions, define success criteria, and calibrate the AI trainers Use internal tooling to assess labeled data and provide feedback to AI trainers Think critically and share recommendations on tooling and process improvements, optimizing for quality, throughput, and AI trainer experience You’ll thrive in this role if: You thrive in dynamic environments. You are comfortable navigating ambiguity, managing shifting priorities, and adapting to fast-paced changes without missing a beat. You’re curious about AI, LLMs, Agents. While not required, an interest or background in these areas will help you connect the dots in our broader mission. You have a can-do a

You will lead a small, hands-on engineering team building the secure, scalable Core Analytics Data Access Platform that accelerates Datadog’s Applied AI and analytics capabilities. The team owns the Data Access Platform — a unified interface that lets AI and analytics teams discover and self-serve production-ready datasets while abstracting underlying systems and embedding required legal and compliance guardrails. In this role you’ll own technical direction, contribute to design and code, and partner closely with Applied AI, Product Analytics, and internal platform teams to provide reliable datasets and APIs for model training and analysis. This role balances day-to-day engineering leadership with long-term platform planning. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Lead a Hands-On Engineering Team: Manage, mentor, and grow a small team of 2–4 data engineers (mix of senior and junior) across Paris and NYC, fostering technical excellence and career development. Own Technical Direction and Delivery: Define architecture, engineering priorities, and the team roadmap for the Data Access Platform, driving implementation of scalable, secure data pipelines and platform services. Contribute to Design and Code: Spend substantial time coding, reviewing, and shipping critical platform components to ensure performance, reliability, and operational excellence. Partner with Internal Stakeholders: Work closely with Applied AI, Internal Product Analytics, product managers, and platform teams to define data contracts, APIs, SLAs, observability, and curated analytical datasets. Ensure Data Security, Governance, and Reliability: Implement access controls, lineage, monitoring, and compliance guardrails to support safe model training and repeatable analytics workflows.

About the Team The People Technology team builds and operates the systems that support how OpenAI hires, develops, and supports its people. The team brings together People Systems and People Innovation Labs, a product engineering group focused on rethinking how we find and retain exceptional talent and help employees do their best work. People Systems owns the company’s core people-technology ecosystem, including platforms such as Workday and Ashby. People Innovation Labs builds new employee and People Team experiences on top of that foundation, including OpenHouse, our internal employee hub, and AI-powered products and automations. Together, we are working toward a model in which our enterprise systems provide reliable data, controls, and core business logic, while employees and managers can complete more of their work through simple, integrated, and AI-native experiences. About the Role We are looking for a People Systems Lead to manage the People Systems team and shape how our core systems evolve. You will be responsible for the reliability and effectiveness of our current environment while helping us move beyond the constraints of traditional enterprise software. This includes stabilizing and improving platforms such as Workday and Ashby, designing the integrations that connect them to the broader technology ecosystem, and partnering with People Innovation Labs to surface workflows through OpenHouse, Slack, and AI-powered experiences. This role requires someone who is comfortable moving between strategy, technical design, and team leadership. You should understand People systems deeply, be able to work through integration and architecture decisions with engineers, and translate complex organizational needs into scalable solutions. You will also manage vendor relationships, develop the People Systems team, and drive alignment across People, Engineering, Finance, Security, Legal, and other partners. This role could be a fit for someone who has grown up in People S

About the Team The Recursive Self-Improvement (RSI) team works across research, engineering, product, and infrastructure to build AI systems that accelerate and ultimately conduct high-quality research at OpenAI. We work to automate real research workflows and improve research productivity by building systems and feedback loops, designing evaluations, and training models to develop missing capabilities. Our work spans the full lifecycle of model training, evaluation, and deployment to help researchers move faster and tackle increasingly ambitious problems. About the Role We’re hiring research scientists , research engineers , and AI systems engineers to work on automating research at OpenAI. This role is based in San Francisco, CA. In this role, you will: Design evaluations for research judgment, hypothesis generation and testing, and long-horizon experiment execution. Turn real research workflows and model failures into data and evaluation flywheels. Improve model research capabilities through agent harnesses, synthetic data, RL environments, and model training. Build and maintain safe, reliable integrations between our models and OpenAI’s research infrastructure. Develop research agents, experiment-orchestration systems, and sandboxed runtimes that support real research workflows. Create metrics and economic models to understand RSI’s current and future effects on research productivity, model capabilities, and the safety of internal deployments. This is a high-ownership role for researchers and engineers who thrive in ambiguity, move fluidly between research and implementation, and turn emerging opportunities into rigorous, reliable, scalable results. You might thrive in this role if you: Have research or engineering experience across LLM training, model evaluations, agent systems, synthetic data, research infrastructure, or large-scale distributed systems. Are a strong generalist who can move between open-ended research and practical implementation, turning ambig

About the Team OpenAI’s GTM Data Science team helps shape how our products are adopted, monetized, and scaled across organizations. We work at the intersection of Product, Go-to-Market, Finance, Research, and Data, turning product usage, customer evidence, and market signals into decisions that grow durable enterprise value. We’re looking for a senior Data Scientist to own the analytical strategy for enterprise knowledge-worker adoption. As ChatGPT Work and Codex become capable of research, analysis, document creation, spreadsheets, presentations, internal knowledge synthesis, and other agentic workflows, you will help determine how these products become embedded in everyday work—not merely tried once. About the Role You will define how we measure activation, retained usage, workflow depth, and value across ChatGPT Work, Codex, and connected enterprise systems. You will explain why adoption succeeds or stalls and identify the product, enablement, and commercial interventions most likely to create durable usage. This is a hands-on, zero-to-one role. You will work through imperfect telemetry, overlapping product surfaces, evolving definitions, and ambiguous business questions. You will partner closely with GTM, Product, Finance, Research, Customer Deployment, Analytics Engineering, and Data Science. Your work is successful when it changes a product, GTM, or investment decision. In This Role, You Will Define a trusted measurement framework for knowledge-worker adoption, including identity, eligible populations, activation, retained usage, penetration, workflow depth, feature adoption, and monetization. Map the knowledge-worker journey from initial exposure through first successful task, repeated workflows, multi-surface usage, and durable adoption. Identify which personas, functions, use cases, product capabilities, and account conditions are associated with deep and retained usage. Design and evaluate experiments and quasi-experiments across onboarding, enablement, wo

About the Team The Infrastructure Engineering function sits within IT and is responsible for reliably building, deploying, and operating critical on prem and hybrid environments that power internal services and critical R&D environments. This is an early, high-leverage technical role focused on applying strong Site Reliability Engineering discipline to environments where uptime, safety, recoverability, and security are non-negotiable. This person helps replace bespoke, one-off infrastructure with standardized infrastructure-as-code building blocks that compound reliability and operational leverage as OpenAI scales. About the Role We are looking for an experienced Site Reliability Engineer working on security infrastructure to design, build, and operate reliable, secure, and scalable infrastructure that underpins identity, access, endpoint, and shared platform services across the company. In this role, you will be a senior technical owner for infrastructure and identity systems end to end, from architecture and implementation through policy enforcement, upgrades, recovery, and day-two operations. You will build durable, production-grade platforms that remove operational friction, enforce security by default, and enable teams to move faster with confidence. This role is well suited for a hands-on senior engineer who thrives in ambiguity, enjoys owning complex systems end to end, and raises the reliability and security bar by replacing fragile implementations with standardized, repeatable infrastructure. This role is based in our San Francisco HQ and requires in-office presence. In this role, you will: Design, build, and operate reliable infrastructure across on-prem, hybrid, shared, and product adjacent environments. Establish standardized infrastructure patterns that replace bespoke implementations with repeatable, auditable, secure-by-default systems. Own the lifecycle of critical infrastructure platforms, including provisioning, deployment, upgrades, patching,