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 |
|---|---|---|
| Performance & Systems Engineer, Codex The role focuses on optimizing the performance and cost of AI systems, specifically the Codex agents, which involve LLM inference, cloud orchestration, and agentic work management. The engineer will hunt down inefficiencies, build tooling for measurement and profiling, and collaborate to improve latency and cost. | ServeAgent | 9 |
| Software Engineer, Inference - Performance Optimization Software Engineer focused on optimizing inference performance across application, model, and fleet layers. This role involves building performance models, analyzing inference workloads, enhancing tooling for bottleneck identification, and collaborating with teams to implement improvements and project future needs. The core of the role is to drive faster and cheaper inference. |
| 9 |
| TL, Research Inference This role focuses on building and optimizing high-performance inference systems for large-scale AI models, translating research ideas into efficient and scalable inference infrastructure. It involves owning core execution paths, distributed inference across multiple GPUs, and optimizing operators and kernels, with a strong emphasis on performance, correctness, and realism for research enablement. | Serve | 9 |
| Inference Technical Lead, On-Device Transformers Lead the implementation of the low-level inference stack for on-device transformer models, including kernel development and runtime systems, while collaborating with researchers and hardware vendors to optimize model architectures for deployment constraints. | ServePost-train | 9 |
| ML Research Engineer - Hardware Codesign Research Engineer focused on hardware-silicon co-design for AI workloads, optimizing numerics, architecture, and technology bets. Involves debugging performance gaps, writing quantization kernels, evaluating numerics via model evals, and prototyping RTL for novel numeric modules. Aims to bridge ML research and hardware development for OpenAI's supercomputing infrastructure. | ServePost-train | 9 |
| Software Engineer, Hardware Software Engineer role focused on building and optimizing the low-level stack for AI supercomputing clusters, including runtimes, kernels, and compiler infrastructure, to orchestrate computation and data movement for distributed training workloads. | Serve | 9 |
| Software Engineer, Inference – AMD GPU Enablement Software Engineer focused on scaling and optimizing OpenAI's inference infrastructure on emerging GPU platforms, specifically AMD accelerators. The role involves working across the stack from low-level kernel performance to high-level distributed execution, integrating internal model-serving infrastructure, debugging distributed inference workloads, and collaborating on high-performance GPU kernels and communication libraries. | Serve | 9 |
| Software Engineer, Accelerators Software Engineer focused on optimizing low-level software for AI accelerators to improve efficiency and performance for large-scale training and inference of AI models, including LLMs and recommender systems. | ServePretrain | 9 |
| Software Engineer, Inference - Multi Modal Software Engineer focused on building and optimizing inference infrastructure for OpenAI's multimodal models (image, audio) at scale, ensuring high-throughput, low-latency delivery and enabling research to production workflows. | Serve | 9 |
| Inference Technical Lead, Sora OpenAI is seeking a GPU Inference Engineer to optimize model serving efficiency, inference performance, and scalability for their multimodal foundation models, Sora. The role involves kernel-level systems, data movement, and low-level performance tuning to support the growth and reliability of AI systems. | Serve | 9 |
| Software Engineer, Model Inference Software Engineer focused on optimizing large AI models for high-volume, low-latency, and high-availability production and research environments. This role involves working with researchers and engineers to bring AI technologies into production, improving the inference stack's performance, and optimizing hardware utilization. | Serve | 9 |
| SOC Architect Seeking an experienced SoC Architect to define and develop next-generation custom AI silicon for edge deployments, focusing on efficient, high-performance SoCs for ML inference. The role involves cross-functional collaboration with internal teams and external partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery. | Serve | 8 |
| Performance Modeling Lead Lead a team to build and own a performance modeling framework for AI infrastructure systems, analyzing tradeoffs across compute, memory, networking, and storage to guide architectural decisions and influence vendor roadmaps. Requires deep knowledge of AI/ML workloads (training/inference) and large-scale distributed systems. | Serve | 8 |
| Software Engineer, Monetization ML Infrastructure Software Engineer to build ML infrastructure for OpenAI's monetization and ads systems. This role involves designing and developing the platform layer for ML models across the full lifecycle, including data pipelines, training systems, model serving, experimentation, and monitoring, with a focus on high-throughput, low-latency advertising workloads. | ServeData | 7 |
| Full-Stack Software Engineer, Compute Foundations This role focuses on building full-stack web applications and backend services to support the operation and optimization of OpenAI's large-scale supercomputing clusters, which are used for frontier model training. The goal is to improve cluster availability, provide better insights into job failures and performance, and enhance resource management. | Serve | 7 |
| Software Engineer, Productivity - Inference Runtime Software Engineer focused on developer productivity for OpenAI's Inference Runtime teams. The role involves scaling engineering systems, safeguards, and developer workflows to ensure reliable, efficient, and safe model serving across various workloads. Key responsibilities include improving tooling and infrastructure for deploy gates, release validation, and observability to enhance model launch processes and inference optimizations. | Serve | 7 |
| Software Engineer, Kernel Performance & AI Tooling Software Engineer focused on kernel performance and AI tooling, working on AI-assisted workflows, developer tooling, observability, and optimizing production kernels for AI workloads. The role involves improving AI-assisted optimization systems and partnering across research and engineering teams. | ServeAgent | 7 |
| ChatGPT Performance Engineer OpenAI is seeking an experienced Performance Engineer to optimize the performance, reliability, and efficiency of their AI systems, including ChatGPT and the OpenAI API. The role involves deep technical expertise in analyzing and optimizing infrastructure and application layers, developing observability tooling, influencing architecture, and leading investigations into performance issues. This is an individual contributor role focused on high-scale distributed systems. | Serve | 7 |
| Software Engineer, Workload Enablement Software Engineer to enable production workloads and end-to-end testing on new platforms for AI infrastructure. This role involves creating test harnesses, porting inference and training workloads, analyzing performance, and characterizing system behavior. | ServePost-train | 7 |
| Hardware / Software CoDesign Engineer - 3P This role focuses on co-designing hardware with vendors to optimize it for AI workloads, specifically for training and inference of large language models. It involves understanding ML techniques, algorithms, and numerical approximations to influence future hardware architectures and improve performance. The engineer will also build system performance models and evaluate potential accelerators. | ServePost-train | 7 |