Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from scalr
Research Engineer
San Francisco, CA - 5 days onsite.
$180K-$220K + equity
My client is an early-stage AI research company building advanced reasoning systems and post-training infrastructure for enterprise AI applications.
The team comes from leading AI labs and startups, with backgrounds across LLMs, reinforcement learning, distributed systems, and applied research.
They are looking for a highly technical Research Engineer to work on:
- LLM post-training and fine-tuning
- RLHF / DPO / reward modeling
- Synthetic data generation
- Evaluation frameworks and reasoning systems
- Distributed training and inference infrastructure
- Agentic AI workflows and production deployments
The role is highly hands-on and suited to someone who has actually trained, evaluated, and deployed models, not just built on top of APIs.
Requirements
- Strong Python + PyTorch experience
- Hands-on LLM training/fine-tuning experience
- Strong ML/AI fundamentals
- Experience working in fast-moving technical environments
- Strong engineering ability and research mindset
Nice to have
- RLHF / evals / synthetic data experience
- Distributed systems exposure
- Publications or open-source contributions
- Experience at strong AI startups or research labs
Source: scalr careers