Research Infrastructure Engineer - Post-Training
Description For Research Infrastructure Engineer - Post-Training
OpenAI is seeking a Research Infrastructure Engineer to join their post-training team, focusing on transforming pre-trained models into user-friendly chatbots like ChatGPT. This role is crucial in building cutting-edge infrastructure and tools that accelerate research and development. The position offers a competitive salary range of $295K-$440K plus equity and comprehensive benefits.
The ideal candidate will work across the entire technology stack, optimizing ML systems, managing job orchestration, and handling data evaluation. You'll be part of a team that builds core infrastructure enabling rapid improvements and frequent model releases. The role requires expertise in either ML system optimization, distributed systems, or full-stack application development.
Working in San Francisco with a hybrid model (3 days in office), you'll collaborate closely with research teams, troubleshoot complex system issues, and implement effective solutions. Key responsibilities include ensuring smooth operation of ChatGPT training systems, debugging ML codebases, and creating reusable Python libraries.
The position offers excellent benefits including comprehensive health insurance, mental health support, generous parental leave, and educational stipends. OpenAI values diversity and maintains an inclusive work environment, committed to ensuring AI benefits all of humanity. This is an opportunity to shape the future of AI technology while working with cutting-edge systems and talented researchers.
The role combines technical challenges with meaningful impact, requiring skills in Python, Kubernetes, and experience with ML systems. You'll work on projects ranging from profiling large model reinforcement learning to redesigning data pipelines for multimodal data, making this an exciting opportunity for someone passionate about advancing AI infrastructure.
Responsibilities For Research Infrastructure Engineer - Post-Training
- Ensure that systems which power ChatGPT training and development run smoothly
- Dive into large ML codebases to understand and debug systems issues
- Work with researchers to build tools for data management, model configuration, evaluation
- Create reusable Python libraries with great abstractions usable across ML projects
- Profile large model reinforcement learning training and identify/address bottlenecks
- Redesign data pipelines to handle diverse multimodal data
- Build front-end evaluation tooling for use across the company
Requirements For Research Infrastructure Engineer - Post-Training
- Experience working in complex technical environments
- Experience debugging ML systems
- Experience with reinforcement learning and transformers
- Experience with Python
- Experience with kubernetes / distributed infrastructure
- Experience with GPUs
- Experience with large scale data systems such as beam or spark
- Must be a team player
Benefits For Research Infrastructure Engineer - Post-Training
- Medical, dental, and vision insurance for you and your family
- Mental health and wellness support
- 401(k) plan with 50% matching
- Unlimited time off and 13 company holidays per year
- Paid parental leave (24 weeks paid birth-parent leave & 20-week paid parental leave)
- Annual learning & development stipend ($1,500 per year)
- Equity
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