Applied AI Engineer
Description
About the company
Our client is a fast-growing software company.
The role
Raydar is recruiting for this role on behalf of our client. Build and evaluate AI agents that run in production, turning new research into working systems that handle live data under strict reliability targets. The role blends hands-on engineering with experimentation, and gives the successful candidate ownership of how results are measured and shipped.
What you'll do
- Design and run applied research programs on model reliability, inference cost and output quality.
- Build evaluation frameworks that judge the full sequence of an agent's actions, not only its final output.
- Contribute to how automated assistants store, look up and use prior information.
- Convert research findings into production infrastructure with measurable impact.
- Help set the direction and priorities of the applied research work.
Requirements
What we're looking for
- Experience at high-growth technology companies or AI research labs.
- A practical record of building sophisticated automated software and networked computing systems.
- Background designing testing tools that measure how automated assistants perform.
- Proficiency in Python programming.
- A background from a top university.
- A clearly demonstrable track record, such as an Olympiad result, a major hackathon win, a widely used open-source project or published AI research.
Bonus points
- Quantitative analytics background, including work in finance.
- Experience with knowledge graph systems, reinforcement learning for agents, production machine learning or post-training of models.
Benefits
Compensation and benefits
- Base salary: $200K to $275K per year
- Equity
- Health, dental and vision coverage
- Life and disability insurance
- 401(k) retirement plan with automatic enrollment
- Unlimited paid time off
- Paid sick leave, company holidays and bereavement leave
- Paid parental leave
- Mental health support and virtual care
- Fertility and family-building support
Location and work model
- San Francisco, California, United States
- On-site, 5 days in-office
- Full-time
Skills
As published by workable · 3 questions
Basics
First name, Last name, Email, Headline, Phone, Address, Photo, Education, Experience, Summary, Resume, Cover letter
Short answers (1)
- Public LinkedIn profile URL (https://www.linkedin.com/in/...)
Pick from a list (2)
- Will you require work authorization of any kind?
- Are you able to work onsite in San Francisco?
