Machine Learning Research Engineer
San Francisco, CA
$250k - $300k + Equity
About the Company:
We're partnering with a well-funded AI startup in San Francisco that's building next-gen conversational AI agents for enterprise use. Their technology is already powering support systems at some of the best-known tech companies, and they've raised over $100M from top-tier investors to continue scaling. It's a fast-moving, highly technical team solving complex problems at the frontier of applied AI.
About the Role:
This is a high-impact role for an experienced ML engineer who thrives at the intersection of research and production. You'll work hands-on with large language models, evaluating, fine-tuning, and deploying them to power autonomous agents that handle nuanced, multi-step conversations. You'll collaborate closely with world-class engineers and product leaders to shape how AI is applied in real-world environments.
What You'll Be Doing:
- Fine-tuning and evaluating LLMs for instruction-following, dialogue, and support tasks
- Building scalable ML infrastructure to support real-time inference and ongoing model improvements
- Experimenting with techniques like RAG, RLHF, and adapter-based fine-tuning to drive performance
- Shipping production-level ML systems with measurable impact on end users
- Contributing to a high-caliber, research-oriented engineering team
What We're Looking For:
- 4+ years of experience in AI/ML engineering or research
- Demonstrated success deploying LLMs or related models in production
- Strong backend and infrastructure skills (low-latency systems, inference optimization, etc.)
- Fast, clean coder with a solid grasp of core ML principles
- Track record of excellence
If you're excited by the idea of building production-grade LLM systems from scratch and want to work with one of the most technically ambitious teams in the space, let's connect.