Research Engineer - Reinforcement Learning
P
Prime IntellectAI infrastructure
Location: San Francisco
Secondary Locations: RemoteFull-Time
SalaryCash Compensation Range of $150-350k, including equity incentives
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Job Details
- Required Skills
- CI/CDMLOps
Requirements
- Have a strong background in AI/ML engineering.
- Bring extensive experience designing and implementing end-to-end pipelines for inference or training large-scale AI models.
- Have deep expertise in distributed inference techniques and frameworks, such as vLLM or SGLang.
- Understand MLOps best practices, including model versioning, experiment tracking, and CI/CD pipelines.
Responsibilities
- Lead and participate in research to build a large-scale synthetic data generation pipeline and orchestration solution.
- Optimize the performance, cost, and resource utilization of AI inference workloads using compute and memory optimization techniques.
- Contribute to open-source libraries for synthetic data generation and distributed reinforcement learning frameworks.
- Publish research in top-tier AI conferences such as ICML and NeurIPS.
- Write approachable technical blogs explaining project outcomes to customers and developers.
- Track advances in AI/ML infrastructure, tools, and synthetic data generation research, and identify opportunities to improve the platform.
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