About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Drive applied machine learning research from early concepts through experimentation to working prototypes. Partner with engineers and designers so findings become dependable product features, and contribute to technical direction as an early hire.
What you'll do
- Lead research projects on language model reasoning, post-training and autonomous agent design.
- Invent techniques that make autonomous model-driven systems more capable, dependable and safe outside the lab.
- Work alongside software and platform engineers to turn prototypes into production features.
- Plan and carry out experiments, measure results against benchmarks and study model behavior to find weaknesses and openings.
- Follow recent literature on reasoning, multi-agent systems, preference-based tuning and tool use, and contribute to papers or open-source projects when it makes sense.
- Influence the research culture and long-term technical plans as one of the first team members.
Requirements
What we're looking for
- A history of leading original research on language model agents, post-training or evaluation, going beyond applying existing methods.
- A PhD or Master's degree in Computer Science, Machine Learning, NLP or AI.
- Deep expertise in at least one area: agentic systems, language model post-training or model evaluation.
- Publications at leading machine learning conferences, where impact and citations count more than degree level.
- Solid grounding in machine learning, covering network design, training approaches and how to structure experiments.
- Proficiency in Python and PyTorch.
Bonus points
- Internships or roles at leading AI research labs.
- Experience training open-weight models.
- Original research ideas and the confidence to challenge colleagues' thinking.
Benefits
Compensation and benefits
- Base salary: USD 280,000 to 350,000 per year
- Equity
Location and work model
- Palo Alto, CA, United States
- On-site, 5 days a week
- Full-time