Artificial Intelligence Research Intern Jobs

About the team The Applied AI Engineering team is responsible for helping developers and enterprises safely and effectively deploy OpenAI technologies in production. We act as trusted technical advisors and thought partners for customers, working side by side with their teams to identify high-value use cases, design practical architectures, and move from prototype to durable deployment. Cybersecurity is one of the most urgent domains where AI can help. Security teams are under pressure to reason across code, logs, infrastructure, tickets, alerts, and vulnerability data faster than ever. As frontier models become more capable, organizations need deep technical guidance on how to evaluate, validate, and safely deploy AI systems in security-critical workflows. About the role We are looking for a Cybersecurity Applied AI Engineer to partner with customers and help them apply OpenAI models, APIs, Codex, and agentic workflows to real cybersecurity use cases. You will work with CISOs, security executives, application security leaders, SOC teams, security engineering teams, and hands-on practitioners to identify where AI can create measurable security outcomes. This is a customer-facing technical role for someone who can move fluidly between executive strategy, practitioner-level cyber depth, and hands-on solution design. You will help customers evaluate and deploy workflows such as secure code review, vulnerability triage, threat modeling, remediation, SOC and incident response workflows, detection engineering, cloud security, GRC automation, and security validation. You will collaborate closely with Sales, Solutions Engineering, Product, Engineering, Research, and Security to turn customer needs into safe deployment patterns, reusable field assets, and product feedback. This role is based in our San Francisco HQ. We offer relocation support to new employees. In this role, you will: Deeply embed with strategic customers as the technical lead for AI-enabled cybersecurity wo

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, advertisers, and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, Research, and external customers to bring new monetization products into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build Ads Manager, the UI platform advertisers use to create, manage, measure, and optimize ad campaigns across OpenAI’s ads ecosystem. This is a foundational role responsible for designing and implementing advertiser-facing products, APIs, tools, and services that connect external customers to OpenAI’s next-generation monetization products. You’ll work across the full technical stack to build intuitive self-serve workflows for small and mid-sized advertisers, as well as scalable APIs and integrations for large enterprise advertisers, agencies, and ad-tech partners who manage campaigns through their own buying platforms or intermediary systems. This includes building advertiser-facing APIs and tooling for campaign management, conversion APIs, pixels, measurement, and insights. You will collaborate deeply with Product, Design, Research, and Go-To

About the Team The GPT Infrastructure team builds systems that turn advances in model inference and optimization into reliable production capabilities. We enable OpenAI workloads to be qualified and optimized across new accelerator platforms without requiring a one-off port and tuning effort for every hardware target. Our work spans distributed systems, model execution, compilers and runtimes, performance engineering, secure partner integrations, evaluation systems, and developer tooling. We build the infrastructure that makes optimization workflows automated, reproducible, and trustworthy. About the Role We are seeking a software engineer to help build the platform that qualifies and optimizes inference workloads across heterogeneous compute environments. You will develop both OpenAI-hosted services and secure partner-side software for running long-lived optimization workflows. These workflows generate candidate kernels, runtime configurations, and serving-stack changes; compile and execute them on target hardware; verify their correctness; measure their performance; and use the results to guide further optimization. You will work across model architecture, distributed execution, compilers, runtimes, networking, and accelerator systems. A central part of the role is turning research prototypes and one-off hardware bring-up efforts into reliable, reusable infrastructure with clear contracts, reproducible results, strong observability, and well-defined security boundaries. Key Responsibilities Design, build, and operate APIs and control-plane services for long-running workload qualification and optimization campaigns, including scheduling, retries, checkpointing, resource budgets, and observability. Build secure partner-side execution and evaluation software that can compile, run, verify, profile, and benchmark candidate artifacts on accelerator hardware. Integrate model workloads, hardware profiles, compiler toolchains, runtimes, serving engines, and distributed-exe

About us Graphcore is a globally recognised leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialised processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Job Summary Working within the Silicon verification team, the silicon verification engineer is responsible for a wide range of tasks within the silicon verification team. This person is responsible for verification activities within Graphcore, helping the silicon team meet the company objectives for quality silicon delivery. The Team The verification team sits within the Silicon design team. We are responsible for ensuring that the RTL created by the logical design team and used by the physical design team matches the architecture specification for Graphcore silicon. Responsibilities and Duties V erification activit i es within the verification team Ensuring good communication between sites Verification planning, specification and closure of functional coverage Providing feedback to architects Test generation and failure diagnosis/triage Contributing to shared verification infrastructure Candidate Profile Essential: verification experience in relevant industry Proven leadership and planning skills Be highly motivated, a self starter, and a team player Ability to work across teams and programming languages to find root causes of deep and complex issues Ability to research along with the knowledge to solve complex problems Presents technical and functional knowledge to design experiments/ projects that contribute to overall

About the Team 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 seeking Software Engineers who can solve complex, high-impact problems across our stack. In this role, you’ll join a nimble team driving the deployment of OpenAI’s technology into new environments and infrastructure that power critical missions in the public sector. You’ll work cross-functionally with product, security, and compliance teams to build the functionality needed to deliver a scalable, reliable platform. You’ll also partner directly with customers to design and build new products and features that create real-world impact. From launching net-new capabilities to optimizing how we serve inference in unique, high-stakes environments, this role offers both breadth and technical depth—giving you the opportunity to shape the future of OpenAI’s technology where it matters most. This role is based in Washington D.C., San Francisco, CA or Seattle, WA. Occasional travel to customer sites is required for this role. This position requires U.S. person status as defined by the applicable government contract. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features end-to-end, both on-premises and in the cloud, for our public sector customers. Partner and directly embed with teams across the business, including engineering, security, and compliance, to enable our products to work within the unique constraints of new environments. Talk to users to understand their problems and design solutions to address them Work with the research team to get relevant feedback and iterate on their latest mo

About the Team OpenAI’s Platform team powers how millions of developers and enterprises build with our models. We provide APIs and agentic solutions used by global startups and fortune 500s. We work closely with product, engineering, design, and go-to-market to build a world-class platform that pushes the frontier of AI capabilities. About the Role As a Data Scientist on the Platform team, you will drive a data-driven culture for OpenAI’s API and B2B solutions. You’ll define the metrics that matter for developer success and enterprise value, measure the impact of new models and features, and partner with PMs and engineers to improve model quality, reliability, latency, and cost. Your work will shape how thousands of products adopt agentic AI. 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 Embed with the Platform product team as a trusted partner, uncovering ways to improve developer experience, reliability, and usage growth Define north-star metrics across the developer funnel (activation, retention, growth), as well as latency/cost guardrails for new features and models Design and interpret A/B tests and controlled rollouts (e.g., new model versions, pricing/limits, new API features, new B2B products) Build source-of-truth dashboards and self-serve data tools for product, engineering, and go-to-market teams Translate product learnings into actionable feedback for Research (e.g., failure modes, eval gaps, model response quality) You might thrive in this role if you have 5+ years in a quantitative role in ambiguous, high-growth environments (platforms, APIs, or B2B products a plus) Depth in SQL and Python, with a track record proposing, designing, and running rigorous experiments Experience defining and operationalizing metrics from scratch (including reliability/latency/cost and safety) Strong cross-functional communication with PMs, enginee

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

About the Team OpenAI’s Client Platform Engineering team builds and operates the platforms that make employee devices secure, reliable, and easy to use. Our work spans device posture and trust, onboarding, application delivery, operating-system updates, fleet telemetry, and employee-facing remediation. We partner with Security, IT, Research, Applied, and specialized engineering teams to reduce friction while protecting OpenAI’s systems and data. About the Role As a Client Platform Engineer , You will build and own agentic solutions that automate OAI fleet operations and reduce employee friction, with measurable outcomes and reliability. You will develop first-party software, integrate commercial and open-source tools, and own changes from design and testing through deployment and production operations. Your work will improve security, reliability, and the employee experience. We’re looking for people who are passionate about automation, endpoint security, and building scalable solutions that improve employee experience. You should have deep experience securing and managing Linux fleets at scale, with strong software engineering skills to automate security controls and fleet operations across environments with different compliance requirements. Your problem-solving mindset and attention to detail will be key to success in this role. In this role, you will: Build the platforms that help employees do their best work on devices they can trust. Own the design, development, deployment, and operation of secure Linux endpoint management systems across environments with different compliance requirements. Create magical employee experiences by building agentic workflows with OpenAI products and models that use fleet telemetry to anticipate issues, guide remediation, and design friction out of everyday work. Make new hires productive from day one, using OpenAI products to simplify device setup, software delivery, and onboarding support. Build secure, reliable workflows with sc

About the team The Applied AI Engineering team is responsible for ensuring the safe and effective deployment of generative AI applications for developers and enterprises. We act as a trusted advisor and thought partner for our API customers, working to build an effective backlog of frontier AI use cases for their industry and drive them to production through strong technical guidance. As an Applied AI Engineer in the Digital Native segment, you’ll work with industry-leading technology companies like Stripe, Uber, and Reddit to bring new AI capabilities into the products their customers use every day. You’ll partner directly with experienced product and engineering teams to turn frontier model capabilities into new features and agentic experiences. The work combines rapid experimentation with the demands of established products: complex systems, real users, and high expectations for quality and performance. Lessons from these deployments inform OpenAI’s product and research teams. About the role You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact – not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our NYC office. 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: Deeply embed with our most sophisticated and technical platform customers, serving a

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering document

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering documentati

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. We are in search of Software Engineer to configure, develop, maintain and support Micron and third-party applications across MFG Application Development Team. You will demonstrate good software engineering principles in all aspects of the development life cycle including the analysis of software requirements, specifications, research, design, document, maintenance, and support. You must have shown ability to build quality software and participate in quality improvement efforts to minimize negative impact resulting from defects, downtime, or performance degradation. You must demonstrate the functional and technical skills vital to switch between various development technologies and merge them to provide the best solution. If these statements describe you, come join Micron Technology, a worldwide leader in the semiconductor industry. Our technology is in the things you use every day—from smartphones to laptops to connected cars. Micron is a world of ideas, memories, and knowledge – accessed, handled, and connected in ways never envisioned. Memory makes it all possible. Required Skill: Hands-on experience with full‑stack software development with strong fundamentals in Core Programming and Object-Oriented Design. Experience with the following technologies: Programming languages / technologies : C#, C++, .NET, .NET Core, WPF, ADO.NET, WebAPI, RESTful services Scripting languages : Perl, Python, PowerShell Database e

About the team The mission of the Applied AI Engineering team is to enable the secure and impactful implementation of GenAI solutions. We serve as technical thought partners and trusted advisors to our clients, ideating high-value use cases and providing the hands-on guidance necessary to drive projects into production. In this role within the Government team, you will empower agencies to evolve their operations through automated content synthesis, advanced search capabilities, and bespoke applications leveraging our latest foundational technologies and models. About the Role We are looking for a hands-on Applied AI Engineer with deep cybersecurity experience and a product mindset to help government and national security customers apply frontier AI to critical cyber missions. You will bring practical expertise in areas such as red teaming, vulnerability research, reverse engineering, threat hunting, and similar fields , ideally developed through work with the defense and intelligence sector. Working directly with cyber operators, security researchers, and engineering teams, you’ll identify high-value applications, write code, build and evaluate AI-powered tools and agentic workflows, and move solutions from prototype into secure operational use. You’ll design architectures using OpenAI models, APIs, and existing security tooling, grounded in customers’ mission requirements and operational constraints. You will collaborate closely with Sales, Solutions Engineering, Applied Research, Product, and Security teams to deliver measurable improvements in cyber capabilities and translate customer experience into better models and products. This role requires frequent on-site engagement at customer and partner facilities across the DMV area, including classified environments. In this role, you will: Work on-site with our clients in the DMV area Own hands-on implementation for government cyber use cases, working alongside account-aligned technical owners, customer engineers, c

About AlphaSense: The world’s most sophisticated companies rely on AlphaSense to remove uncertainty from decision-making. With market intelligence and search built on proven AI, AlphaSense delivers insights that matter from content you can trust. Our universe of public and private content includes equity research, company filings, event transcripts, expert calls, news, trade journals, and clients’ own research content. The acquisition of Tegus by AlphaSense in 2024 advances our shared mission to empower professionals to make smarter decisions through AI-driven market intelligence. Together, AlphaSense and Tegus will accelerate growth, innovation, and content expansion, with complementary product and content capabilities that enable users to unearth even more comprehensive insights from thousands of content sets. Our platform is trusted by over 6,000 enterprise customers, including a majority of the S&P 500. Founded in 2011, AlphaSense is headquartered in New York City with more than 2,000 employees across the globe and offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Come join us! About the Role: Seeking a passionate Senior Engineer to join our Content Engineering team. This team specializes in large-scale content processing using cutting-edge technologies. In this role, you'll leverage AI applications (NLP, LLM) for document understanding, including, but not limited to, document classification, text categorization, data extraction, and semantic similarity. Requirements: Must have - 4+ years of experience as a software engineer, primarily with Python Ideally, you possess an advanced degree (Bachelor's / Master's) in Computer Science, Computer Engineering, or a relevant field with a focus on Artificial Intelligence, machine learning, but equivalent industry experience may be considered 2+ years of hands-on experience building and deploying applications that use Large Language Models (LLMs). E

About the Team Enterprise Verticals builds role-specific ChatGPT Work experiences for high-value enterprise workflows. We combine product engineering, plugins and skills, connectors, data, evaluations, and customer evidence to turn useful demos into reliable daily work. This opening sits within the Technology vertical inside Enterprise Verticals. The group focuses on repeatable workflows for people at technology companies, beginning with functions such as data and analytics, sales, and design, and carries the shared platform needs—tool integration, permissions, quality measurement, and safe rollout—across those experiences. We work closely with Design, Research, GTM, Security, and platform teams, as well as with customers and design partners. Success means that people can reach a trustworthy first result, understand what the system did, and keep using the workflow—not merely that a prototype exists. About the Role We are looking for a full-stack product engineer who can own ambiguous enterprise workflows end to end: understand a customer problem, shape the product, build across frontend and backend, work through platform dependencies, instrument quality, and learn quickly with design partners. You will build across ChatGPT Work surfaces, services, plugins, connectors, and data or permission boundaries when the experience requires it. You will make quality and rollout observable through evaluations, product and operational signals, and clear fallback or rollback paths. This is a product-engineering role for someone who can move between user problems and system details without losing ownership of either. The strongest candidates will be able to turn specific customer evidence into a generalizable product, explain scope and architecture tradeoffs, and carry a feature from an early prototype through a bounded production rollout. In this role, you will: Build and ship role-specific workflows across ChatGPT Work surfaces, services, plugins, and connectors. Turn customer a