Machine Learning Research Scientist

About the company

Our client is a technology company.

The role

Raydar is recruiting for this role on behalf of our client. Develop research systems that propose, test and refine ideas, then move the most promising ones from prototype into shipped software. The position mixes neural network development, reinforcement learning and close work with engineers.

What you'll do

- Work closely with leadership to develop systems that propose, test and refine ideas.

- Team up with software engineers to turn experimental methods into dependable, shipped software.

- Apply reinforcement learning and post-training to large language models to automate parts of the research workflow.

- Keep up with new developments in AI research and automation.

Requirements

What we're looking for

- MS or PhD in computer science, machine learning, AI or a quantitative field, or equivalent research experience.

- Record of publishing in leading AI venues, or comparable experience at an industry research lab.

- Proficiency developing neural network models with gradient-based and reward-based methods, beyond wrapping hosted LLM APIs.

- Post-training or reinforcement learning work on large language models of 15B+ parameters, agent models or genetic algorithms.

- Strong Python skills, with the ability to ship production code independently.

- Track record applying reward-driven training and fine-tuning to neural models.

- Self-directed, comfortable exploring open research directions with minimal supervision.

Bonus points

- Experience at a frontier AI lab or top AI research team.

- Peer-reviewed papers in well-regarded machine learning venues.

- Background operating large multi-accelerator compute jobs or machine learning pipelines at scale.

- Background or interest in automated scientific research.

- Degree from a top-20 institution.

Benefits

Compensation and benefits

- Salary: $200K - $450K

- Equity

- Flexible time off

Location and work model

- San Mateo, CA, United States

- Hybrid, 4 days in-office

- Full-time