AI Frontier · AI lab
Currently tracking 199 active AI roles, down 29% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $230k–$555k (avg $372k).
OpenAI currently has 235 active AI-related job listings. The majority of these roles are in the application stage, accounting for 32% of the total, followed closely by the agents stage at 29%. The dominant function for hiring is Engineering, with 168 positions. Frequent tech tags include model_serving, evals, and agent_orchestration, suggesting a focus on deploying and managing AI models. In the last 30 days, OpenAI posted 50 new AI roles, representing a 14% increase compared to the previous 30-day period.
OpenAI currently has 254 active AI-related roles in our index. The most common open titles are: AI Deployment Engineer (4), Partner AI Deployment Engineer - AWS (4), AI Deployment Engineer - Startups (3), AI Deployment Engineer- Codex (3), AI Deployment Engineer, Startups (2). Most positions are in Engineering and Research.
OpenAI's active AI hiring is concentrated in: application (33%), agents (28%), serving infrastructure (10%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
OpenAI is hiring AI talent in: United States (203 roles), United Kingdom (14 roles), Japan (6 roles), Germany (5 roles).
Job postings at OpenAI most frequently reference: model serving, agent orchestration, evals, llm observability, inference infra.
In the past 30 days, OpenAI has posted 56 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Researcher, Context - Agent Post-Training Researcher focused on post-training of frontier AI agents, improving scaling of compute on context, and owning end-to-end improvements to the post-training stack including RL, data pipelines, graders, reward signals, and evals. The role involves building evals and environments, partnering with product teams, and working on early-training and alignment interventions to shape agent behavior and ship improvements into products. | Post-trainAgent | 10 |
| Researcher, Connectors - Agent Post-Training This role focuses on the post-training of frontier AI agents, specifically teaching them to interface with professional software and tools using code. The researcher will design and run experiments to improve agentic behavior, own improvements to the post-training stack (including RL, data pipelines, graders, reward signals, and evals), build evaluation environments, and work on early-training and alignment interventions. The goal is to enable agents to take useful actions across a user's digital context by connecting them with productivity and enterprise software, ultimately shipping improvements into products. |
| Post-trainAgent |
| 10 |
| Researcher, Computer Use - Agent Post-Training Research role focused on post-training frontier agents, teaching models to operate computers, navigate systems, use tools, and complete complex workflows. Involves designing experiments, owning post-training stacks (RL, data, graders, reward signals, evals), building evals and environments, partnering with product teams, and working on early-training and alignment interventions. | Post-trainAgent | 10 |
| Researcher, Synthetic RL Research Scientist role focused on developing novel reinforcement learning techniques using synthetic data, environments, and feedback to train and evaluate frontier AI models, with a focus on generalization and alignment. The role involves designing experiments, analyzing training dynamics, and integrating research into production pipelines. | Post-trainData | 10 |
| Researcher, Interpretability Researcher focused on studying internal representations of deep learning models to understand model behavior and engineer more understandable representations, with a focus on AI safety and ensuring the safety of powerful AI systems. The role involves developing and publishing research, engineering infrastructure for studying model internals, and collaborating across teams. | Post-train | 10 |
| Research Engineer/Research Scientist, RL/Reasoning Research Engineer/Scientist focused on advancing AI alignment and capabilities using cutting-edge reinforcement learning methods to train intelligent, aligned, and general-purpose agents. The role involves pushing the boundaries of RL research, building next-generation generative models, and deploying them at scale, with a focus on core reasoning paradigms and innovations. | Post-trainAgent | 10 |
| Research Engineer / Research Scientist -Personal AGI, Proactivity Research Engineer/Scientist focused on improving model proactivity and personalization for a collaborative assistant, involving RL, dataset creation, evaluations, and post-training methods, with a strong emphasis on product-driven research and collaboration with product teams. | Post-trainAgent | 9 |
| Researcher, Agent Post-Training, Personality Researcher focused on post-training of AI agents to improve their collaborative personality, involving behavioral research, data creation, reward modeling, and collaboration with product teams to ship improved agent models. | Post-trainAgent | 9 |
| Researcher: Agent Post-Training, API & Power-Users This role focuses on training frontier agents for OpenAI's products, including Codex, ChatGPT, and the API. The researcher will improve agent capabilities, reliability, and product fit for power users and API developers by designing experiments, building training environments, and developing post-training interventions. The role involves working across research, engineering, data, evals, and product to shape agentic model behavior for real-world workflows and API-based applications. | Post-trainAgent | 9 |
| Researcher, Artifacts - Agent Post-Training Researcher focused on post-training frontier agent models to create polished work products like documents and spreadsheets. Owns improvements across RL, data pipelines, graders, reward signals, and evals. Partners with product teams to translate user needs into model improvements and ships capabilities into products. | Post-trainAgent | 9 |
| Researcher, Alignment Training Researcher focused on studying and shaping aligned behavior in frontier AI models through various training stages (pre-training, mid-training, post-training). The role involves developing synthetic data methods, building evaluation loops, designing data generation pipelines, and creating experiments to distinguish durable learned behavior from artifacts. Collaboration with other teams is key to translate research insights into better model behavior. | Post-trainData | 9 |
| Researcher, Alignment Science Research role focused on intent alignment for AI models, including instruction following, honesty, calibration, and robustness. Involves designing and running experiments, training models with RL, developing evaluations for failure modes, and integrating successful techniques into model development. Aims to produce publishable research and deployable techniques. | Post-trainEval Gate | 9 |
| Research Engineer/Scientist - Human Alignment, Consumer Devices Research Engineer/Scientist focused on RLHF and post-training for personalized, multimodal AI systems within the Consumer Devices group. The role involves building learning and evaluation foundations for adaptive models, working on reward modeling, preference learning, and long-horizon evaluation to improve model behavior in realistic user settings, with a strong product grounding. | Post-trainAgent | 9 |
| Research Engineer / Machine Learning Engineer - Applied Voice Research Engineer role focused on designing, building, and optimizing state-of-the-art speech models (speech-to-speech, transcribing, text to speech) and transforming research breakthroughs into tangible OpenAI speech products. Involves collaboration with cross-functional teams, implementing scalable data pipelines, and ensuring models are production-ready. | Post-trainServe | 9 |
| Research Engineer, Privacy Research Engineer focused on integrating privacy into AI systems, developing and deploying privacy-preserving ML algorithms, measuring robustness against privacy attacks, and defining privacy standards for the ML lifecycle. | Post-trainData | 9 |
| Research Engineer / Research Scientist, Post-Training Research Engineer/Scientist focused on post-training of pre-trained models for deployment in products like ChatGPT and API. The role involves owning a research agenda to improve model capability and performance, collaborating with other teams, building robust evaluations, and implementing/debugging code. Requires strong ML engineering skills, research experience, and understanding of machine learning applications and model evaluations. | Post-trainEval Gate | 9 |
| Technical Lead, Safety Research This role is a Technical Lead for Safety Research at OpenAI, focusing on advancing AI safety and alignment. The team works on implementing robust, safe behavior in AI models, developing new evaluations for misalignment, and supporting human oversight. The lead will set research directions, drive exploratory research, and collaborate across teams to ensure strong safety results. Key responsibilities include setting research strategies, coordinating with cross-functional teams, evaluating model safety, and conducting research on topics like RLHF, adversarial training, and robustness. The role requires a strong track record in AI safety research, leadership experience, and a deep understanding of deep learning. | Post-trainEval Gate | 9 |
| Researcher, Health AI Researcher focused on AI safety and alignment techniques for healthcare applications, aiming to improve model behavior, knowledge, and reasoning, and integrate these methods into core training and product launches. | Post-trainEval Gate | 9 |
| Researcher, Alignment Research role focused on ensuring AI systems are safe, trustworthy, and aligned with human values, developing methodologies for robust intent following, and integrating human oversight. | Post-trainEval Gate | 9 |
| Researcher, Robustness & Safety Training Researcher focused on AI safety, specifically in training models for robustness, alignment, and adversarial resistance using techniques like RLHF. The role involves setting research directions and implementing improvements in OpenAI's products. | Post-train | 9 |
| Model Policy Manager, Chemical & Biological Risk This role focuses on developing and implementing policies for AI models concerning chemical and biological risks. It involves creating structured policy frameworks and taxonomies to guide safe model behavior, translating biosecurity expertise into actionable model policies, and identifying emerging risk vectors. The role sits at the intersection of biosecurity expertise, AI safety research, and policy design, aiming to reduce misuse risks while enabling beneficial research. | Post-trainEval Gate | 7 |