San Francisco, CA · On-site · Full-time Compensation: $150,000–$300,000 + 0.5%–1% equity
About the Company
Our client does LLM interpretability and context-optimization research, building custom machine-learning models that analyze and compress token contexts before they reach the underlying model. The result is roughly a 50% inference-cost reduction, lower latency, and measurably higher accuracy for the enterprises and scale-ups integrating LLMs into their products. About seven months old, it already serves roughly 1,000 customers and is well-backed by top-tier investors and notable operators.
Founded 2025 · 1–10 people (Seed) · Industry: AI Tools
The Role
As an ML Researcher, you own a slice of one of the most interesting open problems in applied AI: figuring out what information inside an LLM context actually matters, and how to represent it more efficiently. A high-autonomy, high-output role for someone who wants to run a large volume of experiments, reproduce papers, and see their research ship into a production system used by real customers.
Tech stack: Transformers, custom model-training loops (data + architecture + training + evals), NVIDIA B200s and large-scale GPU clusters, eval infrastructure.
Requirements
- Prioritizes production impact over publication metrics
- Owns the model-training stack end to end — data, architecture, training, evaluation, and shipping
- Has trained models from scratch with genuine end-to-end ownership
- Strong ML fundamentals — transformers, mechanistic interpretability, LLM research
- A high-agency, self-directed, experiment-driven researcher (not RAG- or chatbot-only)
- A spiky profile — exceptional pre-career achievement in competitions, research, or founding
- On-site in SF at high intensity in a hacker-house environment
Nice to Haves
- Pretrained a transformer model
- Serious post-training or RL experience on transformers
- Built a novel architecture or training method with results
- Shipped trained models into production systems
- Experience in research labs, startups, or scale-ups
- Exceptional early-career achievement
Why Join
- Research that ships: success is measured by getting a model into a product used by ~1,000 customers, not by publications
- Own a frontier problem end to end: full ownership of a slice of LLM context compression and mechanistic interpretability
- High autonomy: every researcher directs their own agenda with minimal structure, reporting to the founder
- Serious backing and pedigree, plus real compute (NVIDIA B200s and large-scale GPU clusters)
- Everything covered: SF housing, food, laundry and cleaning, healthcare and dental, significant equity, visa sponsorship, and company off-sites
Details
- Location — San Francisco, CA
- Work policy — On-site, high intensity
- Compensation — $150,000–$300,000 + 0.5%–1% equity
- Visa sponsorship — Available (H-1B, O-1, OPT)
- Employment type — Full-time