Artificial Intelligence Research Intern Jobs

The Complex Assets Product Manager is a senior position within Product Management, responsible for day-to-day product management for complex financial instruments, setting strategy, and providing direction within the Complex Assets domain. The role requires a deep hands-on working knowledge of Complex Assets, including OTC derivatives, Exchange Traded Derivatives, and Portfolio Swaps, within a financial services business. Additionally, this role will be responsible for the development of product plans, strategies, and tactics while coordinating product lines through product life cycles in coordination with the broader Product Management team. This role will leverage broad Complex Assets domain knowledge, deep experience influencing product, operations, design, and IT architecture change. Timely execution, seamless business and client change are extremely important to ensure continued growth and expansion of relationships with strategic clients in the complex assets space. What you’ll do Oversee strategic roadmap, development, launch, and marketing to gain maximum benefit from each product Oversee day-to-day product management for core products such as product delivery, client experience, and client communication strategies as well as help the team prioritize, negotiate, and remove obstacles to achieve business results Execute client value propositions, positioning, segmentation, pricing, targeting, channel strategies, and competitive differentiation to achieve preferred status as a partner to Citi clients Develop plans and execute functional strategies for a country, multiple countries, region, or business requiring coordination and integration across units as well as provide input into strategic decisions affecting job family or function within a region or business Manage client and competitor market research, develop product innovation roadmap, and address fundamental trial

About the Role OKX is looking for a Senior Director of AI to lead both people and product — building and managing a high-calibre AI team while staying deeply involved in the design, evaluation, and production deployment of autonomous agent systems. This role calls for a leader who leads by doing: technically grounded, sharp on product judgment, and able to translate both into tangible business outcomes. What You'll Do Team Leadership — Build, manage, and develop a team of AI engineers and researchers; own hiring, growth, and performance across the function Agent Product Delivery — Lead end-to-end delivery of autonomous AI Agent products, covering the full lifecycle from requirements and architecture through to production operations Eval-Driven Development — Establish benchmark-driven evaluation frameworks that replace manual iteration with quantifiable quality signals across agent systems Agent Harness Design — Design and implement end-to-end Agent Harness infrastructure to ensure agent stability and reliability in complex, real-world scenarios LLM Orchestration — Orchestrate creative reasoning steps alongside deterministic guardrails, finding the right balance between flexibility and control Engineering Workflow Integration — Embed AI Agent capabilities deeply into core products and engineering pipelines, improving both developer productivity and business value Cross-functional Alignment — Collaborate with product, engineering, and business teams to ensure technical direction stays tightly aligned with strategic priorities What We're Looking For Must-have Master's or PhD in Computer Science, Artificial Intelligence, or a related field (PhD preferred) 10+ years of experience in AI/ML research, productization, or platform development, including core technical or leadership roles at globally recognized technology companies Deep expertise in LLMs and Generative AI, deep learning, reinforcement learning, recommendation systems, and related areas Proven track record of t

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. Responsibilities and Tasks: Develop and refine CMP processes to deliver outstanding performance and yield. Collaborate with cross-functional teams to successfully implement process improvements. Conduct rigorous data analysis to determine the root cause of process variations and implement corrective actions. Ensure all processes strictly align with industry standards and safety regulations. AI Relevant Job Responsibilities: - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and operational excellence, Micron delivers a rich portfolio of high-performance DRAM,

About the Team The Safety Training research team aims to fundamentally advance our capabilities for precisely implementing safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to train nuanced safety behaviors, how to make the model robust to bad actors, how to address privacy and security risks, and how to make the model trustworthy in safety-critical situations. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role We’re seeking a researcher to train and evaluate models for U.S. government use, with a focus on national security applications. You’ll advance safety post-training and robustness, helping models follow nuanced policies while preserving their usefulness and capabilities. In this role, you will: Research and implement methods for safety training, reinforcement learning, and adversarial robustness. Develop evaluations, identify model failure modes, and use findings to improve training. Work with research, engineering, security, and policy partners to support safe, reliable deployment. You might thrive in this role if you: Bring 4+ years of relevant AI safety research experience, including RLHF, adversarial training, or robustness. Have a degree in computer science, machine learning, or a related field, and strong deep learning research or engineering skills. Have experience improving model safety for deployment and enjoy collaborative research. Are motivated by OpenAI’s mission and the responsible use of AI in safety-critical settings. Security Requirements Active TS/SCI clearance or equivalent. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefi

About the Team The Applications Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. 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 The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

About the Team The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. 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 The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. This role is based in San Francisco, CA. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely depl

NVIDIA is a leading artificial intelligence computing company, and we are paving the way with innovations in self-driving cars, machine learning, supercomputing, gaming, and visualization. We give automakers, tier-1 suppliers, automotive research institutions, and start-ups the power and flexibility to develop and deploy breakthrough artificial intelligence systems for self-driving vehicles. Our unified computing architecture enables training deep neural networks in the data center, and then seamlessly runs them on NVIDIA DRIVE Platforms inside the vehicle. The Hypervisor and RTOS Team within NVIDIA DRIVE Software plays a critical role in NVIDIA's expansion into the world of artificial intelligence and autonomous vehicles. Our job is to facilitate the sharing and separation of system resources while achieving real-time, safety, and security requirements. We develop Hypervisor and RTOS with a strong focus on automotive quality, safety and security needed for the real-time, highly available system level components of world-class Autonomous Vehicles. We are making extensive use of formal methods to automate our workflow and increase the quality of our SW. We are hiring now for the position of Senior System Software Engineer for Hypervisor and RTOS What you’ll be doing: Design and develop new features for RTOS and hypervisor software stack. Bring up and optimize RTOS and hypervisor stacks on new NVIDIA Tegra SoCs. Develop high-integrity software using best-in-class engineering, safety, and security practices. Debug complex system-level issues across hardware, firmware, RTOS, and virtualization layers. Lead team-wide technical initiatives by building alignment, coordinating execution, and driving them to completion. What we need to see: BS, MS in CS/CE/EE or a related engineering field or equivalent experience </

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive. With a billion rides per year and counting, Lyft is solving hard problems in a rapidly growing domain with a lot of data and creative solutions in Rider, Marketplace, Growth, and beyond. While traditional approaches to optimization and problem decomposition are sufficient to disrupt transportation, building a next-generation platform for low-cost, ultra-immersive transportation to improve people's lives warrants modern ML utilizing peta-byte scale data. Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. If you are a critical thinker with experience in machine learning workflows and LLMs, passionate about solving business problems using data and working in a dynamic, creative, and collaborative environment, we are searching for you. We are seeking a Senior Machine Learning Engineer to join the Rider Applied AI team and lead the design, development, and deployment of state-of-the-art machine learning and artificial intelligence systems. This role requires a strategic thinker who can balance high-level system architecture with hands-on technical implementation. You will collaborate across teams to shape the future of ride-sharing by leveraging AI, Machine learning and Data science. Responsibilities: Model Development & Research: Design, build, and deploy machine learning models for real-time applications, including translating state-of-the-art research into production-ready solutions. System Design: Architect scalable, reliable ML pipelines that integrate seamlessly with existing backend systems. Innovation & Applied Research: Stay ahead of the curve by exploring emerging algorithms, technologies (such as LLMs and LLM-based applications), and frameworks — critically eva

About the Team Our team builds classification and evaluation systems that give post-training and research teams fast, reliable feedback on model behavior. We combine machine learning and production engineering to make these capabilities accurate, efficient, and useful at scale, helping researchers assess changes and improve models and products. We work closely with research teams to develop useful measurements and make them practical to run. Our work spans classifier development, rigorous evaluation, and efficient production inference, with ownership from initial experimentation through deployment and continued improvement. About the Role We’re looking for a machine learning engineer to develop new classification and evaluation capabilities and bring them into production. You’ll help turn open-ended questions about model behavior into well-defined ML problems, build methods that address them, and establish how reliably those methods work. This role combines traditional machine learning, model evaluation, and real-time engineering. You’ll own classifiers throughout their lifecycle, including supervised fine-tuning, distillation, evaluation, deployment, and production inference. You’ll work closely with researchers to identify valuable problems and with software engineers to make promising approaches useful at scale. In this role, you will: Build, deploy, and operate production classification and evaluation systems that provide useful feedback to post-training and research teams. Optimize production inference, including model serving, batching, caching, throughput, latency, compute utilization, and cost. Train and optimize classifiers using supervised fine-tuning and distillation, validating quality and efficiency before deployment. Own the reliability and observability of deployed classifiers, diagnose production issues, and improve their performance over time. Design rigorous evaluations that assess accuracy, calibration, generalization, and potential measurement bi

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 Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: Profil

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 As a Research Engineer in OpenAI's Monetization Group, you will have the opportunity to work with some of the brightest minds in AI. You'll contribute to deploying state-of-the-art models in production environments, helping turn research breakthroughs into tangible solutions. If you're excited about making AI technology accessible and impactful, this role is your chance to make a significant mark. In this role, you will: Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. Optimize and Scale: Implement scalable data pipelines, optimize mod

About the Team The Future of Computing Research team is an applied research team within OpenAI’s Consumer Devices group. We study how AI systems perceive people and their surroundings, and we turn that research into capabilities for future products. Our work spans machine learning, sensing, and hardware, with a focus on building systems that work beyond controlled environments. About the Role We’re looking for a machine learning engineer to help shape how future AI systems understand the physical world and the people in it. The role focuses on multimodal perception and authentication, bringing together signals from cameras, microphones, and other sensors. You’ll work with specialized perception models and larger multimodal models, and partner with hardware, firmware, software, and product teams to bring new research into real-world systems. This role is based in San Francisco. We work in the office three days per week and offer relocation assistance. In this role, you will: Research and develop multimodal perception and authentication methods across visual, audio, and other sensing signals. Explore how specialized perception models and larger multimodal models can work together. Design data, training, and evaluation approaches that improve performance in real-world conditions. Study model behavior, robustness, and failure modes across sensing, data, and deployment environments. Integrate and validate new capabilities in real-time or resource-constrained systems. Work with hardware, firmware, software, and product teams to turn research into working systems. You might thrive in this role if you: Have a strong background in computer vision, audio or speech machine learning, multimodal learning, or sensing. Have experience developing specialized machine learning models, larger multimodal models, or both. Have brought research ideas into practical systems, prototypes, or products. Know how to design experiments, build evaluations, and investigate model behavior. Have wo

Chicago Trading Company (CTC) is a premier proprietary trading firm specializing in options market making. Our collaborative culture fuels innovation in quantitative research, systematic trading strategies, and cutting-edge trading technology. For over three decades CTC has provided critical liquidity across derivatives exchanges worldwide - making them fairer, more transparent, and more efficient. We strive to be the most innovative firm in the industry today, tomorrow, and long into the future while upholding ethical excellence. We believe that CTC makes a positive impact on the markets, the lives of our employees, and all the communities to which we belong. Started in 1995 by a team of forward-thinking Traders, we are proud to call ourselves an industry leader that keeps making markets and each other better. Are you excited by the opportunity to be part of a dynamic trading environment that values teamwork and collaboration? Do you thrive in an innovative atmosphere? If so, we encourage you to consider Chicago Trading Company! The Role The Quant Trading Associate (QTA) role is our entry-level position within our Trading and Quant organization and gives you broad exposure to the whole business as you work towards graduating from the Associate Program and assuming a role as a Quant Trader or Quant Researcher. As a QTA, you will work in a high-impact role as a member of a trading or quantitative team. You will play a vital part in identifying trading opportunities and impacting your team through dynamic problem solving — including trade execution, strategy formulation, back-testing, data analysis, and the modeling and pricing of traded financial derivatives — while communicating with traders, risk managers, software engineers, and quants throughout the trading day. You will learn all aspects of the trading and quant operation and work towards a role that generates trading revenue or drives strategy development for the team. In addition to the

About the team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing together world-class scientists, engineers, and business leaders to translate frontier research into real-world impact. Within OpenAI, the Go-to-Market organization helps customers understand, adopt, and scale our products across their businesses. The team includes Sales, Solutions, Support, Marketing, Partnerships, and Strategic Pursuits professionals who work together to bring the benefits of AI to organizations globally. About the role We are hiring a Senior Specialist Seller to join the Strategic Pursuits team and lead priority opportunities generated through the joint AWS and OpenAI co-sell motion. You will partner closely with Account Directors, AWS field teams, and cross-functional stakeholders to identify, shape, advance, and close high-value strategic enterprise engagements. This role is ideal for a senior seller with deep experience in enterprise technology, AI, cloud, or complex transformation sales motions. You should be comfortable operating in executive-facing environments, aligning multiple stakeholders, and turning customer priorities into commercially compelling and technically credible opportunities. This role is based in San Francisco, Seattle, or New York. We operate on a hybrid model of 3 days per week in office and offer relocation support. We are also open to remote candidates based in the United States. In this role, you will: Lead commercial execution of priority AWS/OpenAI co-sell opportunities across strategic enterprise accounts. Identify and qualify high-potential opportunities focused on GenAI adoption, frontier platform use cases, and enterprise-wide transformation. Partner with AWS and OpenAI field teams to align account strategy, messaging, stakeholder mapping, and execution plans. Develop customer-facing value propositions that connect OpenAI capabilities with business priorities and