Posted 4 weeks ago

Research Engineer

San Francisco, California, United States 🇺🇸
  • Onsite
  • Full Time

Job description

About the company

Our client is a fast-growing technology company.

The role

Raydar is recruiting for this role on behalf of our client. Build and run evaluation and reinforcement learning task pipelines for coding-focused AI models, working directly with external customers from the first day. The role grows over roughly six months from hands-on engineering into leading a small team of engineers.

What you'll do

- Design and build coding evaluations and reinforcement learning tasks, along with the pipeline that produces them.

- Run evaluations of leading AI models against an internal benchmark and a set of representative tasks.

- Partner directly with customers, quality-checking deliverables and shipping to specification.

- Build reinforcement learning tasks hand in hand with customers as the engagement matures.

- Grow into leading a team of engineers over the first several months.

Requirements

What we're looking for

- Solid working knowledge of reinforcement learning, coding-focused RL, evaluations, harnesses, benchmarks and post-training; this is a firm requirement.

- A blend of research intuition and the engineering skill to build tasks and evaluations.

- Prior experience at a data company, or concrete self-driven evidence such as a benchmark you built or a post-training side project.

- High energy, strong drive and a hunger to learn and do as much as possible.

- High agency, a strong work ethic, integrity and an earnest attitude toward learning.

- Roughly 1 to 5 years of relevant experience.

Bonus points

- Research experience at a strong lab or university.

- Interest in starting a company someday.

- Relocating to the Bay Area from outside the region and a deep curiosity about AI.

Benefits

Compensation and benefits

- Base salary: USD 150,000 to 200,000 per year

- Equity

- Health insurance

Location and work model

- San Francisco, California, United States

- On-site, in office

- Full-time