OpenAI
AI Frontier · AI lab
- HQ
- San Francisco, US
- Founded
- 2015
- Size
- 5,000+
- Website
- openai.com
- Blog
- openai.com
Products
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 |
|---|---|---|
| RE/RS, Data Understanding - Foundations This role focuses on research and development of high-quality datasets for large model training at OpenAI. Responsibilities include synthesizing data, building VQ representations, and processing/filtering data. The role involves treating data quality as a research problem, developing new methods for data selection and transformation, and designing experiments to understand data's impact on model learning. The goal is to translate research into scalable data processing pipelines. | DataPretrain | 9 |
| RE/RS, Data Understanding (MM) This role focuses on preparing, curating, synthesizing, and understanding multimodal data (images, audio, video) at scale for large model training. It involves research and production problems related to data pipelines, quality filters, and using models for data preparation, with an emphasis on measuring dataset impact on model performance. |
| Data |
| 9 |
| RE / RS - Foundations, Search Research role focused on embedding retrieval and agentic search, developing foundational technology for future frontier models. Involves designing new embedding training objectives, scalable vector store architectures, and dynamic indexing methods, with potential for publication and integration into OpenAI products. | DataAgent | 9 |