Member of Technical Staff – Reinforcement Learning
Liquid AI
full-time
Posted on:
Location Type: Hybrid
Location: San Francisco • California • United States
Visit company websiteExplore more
Job Level
About the role
- Profile, optimize, and scale RL training runs to reduce iteration time
- Integrate new optimization techniques as they emerge from the research community
- Design and implement tools and environments that test the boundaries of model capabilities
- Turn proof-of-concept ideas into robust training pipelines and best-in-class models
Requirements
- Strong Python and PyTorch proficiency, with hands-on experience optimizing training pipelines
- Hands-on experience with reinforcement learning and the ability to translate optimization techniques from theory into practical implementations
- Track record of integrating research ideas into robust, maintainable code
- Experience with frameworks like DeepSpeed, FSDP, or vLLM for efficient model training and inference
- Experience working with data pipelines, including curation, validation, and analysis to support post-training objectives
- Contributions to open-source machine learning projects
- M.S. or Ph.D. in Computer Science, Electrical Engineering, Mathematics, or a related field
Benefits
- The opportunity to work directly on state-of-the-art AI systems at one of the most advanced AI companies in the world
- A fast-paced, collaborative environment where your work has direct impact on model performance and product capability
- The satisfaction of knowing your craftsmanship helps define the next frontier in AI
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonPyTorchreinforcement learningDeepSpeedFSDPvLLMdata pipelinesmodel trainingmodel inferenceoptimization techniques
Certifications
M.S. in Computer SciencePh.D. in Computer ScienceM.S. in Electrical EngineeringPh.D. in Electrical EngineeringM.S. in MathematicsPh.D. in Mathematics