Latest ML Engineering jobs at OpenAI

Build research infrastructure and tooling that enables AI models to design silicon, including reinforcement learning environments, EDA integrations, evaluations, and experiment workflows. The role requires strong software engineering fundamentals and comfort working across research, tooling, and chip-design systems.

Build and deploy AI-powered products for digital-native customers, taking systems from experimentation through production and scale. The role requires strong Python skills, hands-on production engineering, systematic AI evaluation, and the ability to navigate reliability, security, governance, and customer impact.

Build and deploy AI-powered software development workflows with enterprise engineering organizations, taking Codex use cases from prototype through production and scaled adoption. The role requires strong hands-on software or AI systems experience, Python proficiency, systematic evaluation skills, and fluent Japanese and English.

Build and optimize the production LLM inference runtime for frontier models on OpenAI’s custom silicon. The role spans scheduling, distributed execution, memory and KV-cache management, performance tooling, and hardware-software co-design.

Develop multimodal perception and authentication systems combining visual, audio, and other sensor signals for real-world AI products. The role requires machine learning expertise, practical research-to-system experience, and proficiency in Python and PyTorch with comfort in C++.

Build and optimize OpenAI’s inference stack for AWS Trainium across high-performance kernels, compilers, runtimes, and model execution. The role requires systems programming and accelerator experience, with opportunities to solve end-to-end performance problems for frontier-scale AI models.

Build production machine learning systems for model customization, post-training, evaluation, and AWS-native API integration. The role requires 7+ years of relevant engineering experience and expertise in deep learning, transformers, LLM fine-tuning, and production ML infrastructure.

Design and deploy scalable safeguards that mitigate cybersecurity misuse by frontier AI models across OpenAI product surfaces. The role requires deep learning and transformer expertise, software engineering fundamentals, LLM fine-tuning experience, and cross-functional collaboration.

Develops reinforcement learning, memory, and personalization capabilities for frontier models, including long-horizon evaluations and research code. The role requires strong RL research experience, rapid iteration, and the ability to translate rigorous research into product impact.

Build and improve production AI agent systems for OpenAI's GTM workflows. Own the end-to-end improvement loop using feedback, evaluation, experimentation and backend services to drive measurable gains in customer engagement, pipeline and team productivity. Requires 4+ years building reliable LLM-powered production systems plus strong product judgment.

Research Engineer/Scientist on OpenAI's Personal AGI Model Experience team, shaping ChatGPT's character, behavior, and human-AI interactions through research, human data, evaluations, reward models, and post-training. Requires strong ML engineering and research experience with large models.

Build and operate an automated inference optimization platform spanning control planes, secure partner-side runners, compilers, and evaluation systems for new accelerator hardware. Requires 8+ years building large-scale distributed systems with strong performance and systems expertise.

Research Engineer on OpenAI's Privacy team designing and prototyping privacy-preserving ML algorithms like differential privacy and federated learning at scale. Requires hands-on PETs experience, fluency in PyTorch/JAX, and a track record implementing or publishing novel privacy work.

Principal engineer on OpenAI's Codex Cyber team building AI-powered security products for trusted defenders. Define roadmaps, shape model training and safeguards, build evaluations for cyber capabilities and risks, and translate frontier research into production tools while collaborating across product, research, safety, and external partners.

Research Engineer/Scientist shaping personalities and behaviors of personalized AI models like ChatGPT using RL, reward modeling, synthetic data, and post-training methods. Requires strong ML engineering and research experience with large models.

Train frontier models to generate polished artifacts (docs, spreadsheets, slides) by owning post-training improvements across RL, data, evals, and alignment. Requires strong ML fundamentals and hands-on LLM/RL experience.

Train frontier models to operate computers, browsers, and desktops. Design experiments, build evals, own post-training pipelines (RL, data, graders), and ship improvements into OpenAI agents.

Train frontier agents to interface with professional software via code, APIs, and structured integrations. Design experiments, own post-training improvements (RL, evals, data), and ship capabilities into major model runs.

Context Researcher on the Agent Post-Training team scaling compute on context for frontier agent models. Designs experiments, owns post-training improvements, builds evals, and ships capabilities into Codex and ChatGPT.

Help shape OpenAI agent personality by turning qualitative collaboration insights into evals, training data, reward signals, and model improvements that reach production.

Improve agentic model capabilities, reliability, and product fit for power users and API developers through evals, training data, and post-training interventions.

Research Engineer/Scientist improving model capabilities for personalized AI experiences. Focus on tool-use, instruction following, evaluations, and training improvements. Requires strong ML engineering and research experience.

Improve capabilities, reliability, and product fit of OpenAI's agentic models through research, infrastructure, evals, and training. Work across RL, data, model behavior, and product integration for frontier agents.

Lead ML engineering on OpenAI's Integrity team to build, deploy, and optimize LLMs and classifiers for content understanding, abuse prevention, and platform safety. Requires advanced degree, deep learning expertise, and LLM fine-tuning experience.

Research and develop improvements to models' personalization and agentic capabilities through reinforcement learning, dataset creation, and post-training methods. Requires strong ML engineering skills and research experience with novel models.

As a Software Engineer, you will build and design the machine learning infrastructure for OpenAI's monetization and ads systems. This involves developing large-scale data pipelines, model training platforms, real-time inference systems, and experimentation frameworks to support high-throughput, low-latency advertising workloads.

Build and maintain infrastructure for large-scale RL training runs of frontier OpenAI models. Debug across training, inference, and distributed systems while supporting research integrations.

Hands-on senior software engineer focused on maintaining and improving ML training infrastructure, debugging training systems, and unblocking researchers on the robotics team.

Builds core agent harness for Codex AI agents, enabling safe tool use, code execution, and long-horizon tasks in production. Designs systems for sandboxing, evaluation, observability, and performance optimization across ML workflows and infrastructure.

Models inference performance across application, model, and fleet layers using microbenchmarks to build cost-to-serve estimates. Analyzes workloads end-to-end, enhances bottleneck detection tools, and collaborates on optimizations for latency, throughput, and cost.

Software Engineer enabling production AI workloads on new hardware platforms through porting, benchmarking, stress testing, and performance optimization. Requires 5+ years in ML systems, distributed training, PyTorch, and RDMA/NCCL expertise.

Develops and improves Codex AI agents for real-world software engineering tasks, focusing on performance, reliability, and integration with research and product teams. Requires strong Python, ML/LLM experience, and skills in evaluation, prompting, and debugging production failures.

Deploys state-of-the-art ML models and fine-tunes LLMs in production to enhance platform integrity and safety against adversarial threats. Requires Master's/PhD, deep learning expertise, PyTorch/TensorFlow proficiency.

Build and own autonomous agentic systems for customer-facing revenue and marketing workflows, partnering with sales and marketing teams. Requires 4+ years experience in software/ML engineering, full-stack skills in Python/JavaScript, and production systems expertise.

Designs and scales distributed data infrastructure for large-scale multimodal AI training and evaluation. Collaborates with researchers to build reliable, high-performance systems in a fast-paced environment.

Partners with customers to design, prototype, and scale AI-enhanced coding workflows using OpenAI Codex. Serves as technical expert, leads workshops, builds demos, and influences product direction. Requires 5+ years in technical consulting or solutions engineering.

Develops and optimizes internal distributed ML training framework to boost hardware efficiency and enable researchers to experiment with new AI models. Requires strong Python skills, systems understanding, and passion for performance tuning.

Partners with government agencies to develop and deploy GenAI applications using OpenAI API, from strategy to production. Requires 7+ years public sector technical consulting, TS/SCI clearance, and ML implementation experience.

Build and optimize high-performance inference infrastructure for OpenAI's multimodal models handling image, audio, and other non-text inputs at scale. Collaborate with research and product teams on low-latency production systems using GPU workloads and inference tooling.

Leads GPU inference engineering for Sora, optimizing model serving efficiency, kernel-level performance, and scalability. Collaborates with research and product teams to build reliable infrastructure for multimodal AI models.

Build and maintain anti-abuse and content moderation infrastructure to ensure AI safety. Collaborate with engineers on AI alignment techniques, incident response, and risk mitigation using Python and cloud tools.

Optimizes large AI models for high-volume, low-latency production and research environments. Collaborates with researchers and engineers on inference stack performance, requiring 5+ years experience with PyTorch, GPUs, CUDA, and distributed systems.

Develop and deploy retrieval and search algorithms for OpenAI's API and ChatGPT, collaborating with research teams on production systems for millions of users. Requires experience with ML systems, vector databases, and large-scale search.