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Machine Learning Engineer

Raydar · San Francisco, CA, United States · Onsite

  • Professional Services
  • 11–50 employees
  • Santa Monica, California

Strong hiring record · median 32 days open

100100

Hiring signal

Open

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Machine Learning Engineer at Raydar. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

About the company

Our client is an early-stage software company.

The role

Raydar is recruiting for this role on behalf of our client. Serve as the first engineering hire, building reinforcement learning environments and production AI agents. Work side by side with the company's leadership to shape technical priorities, and step into running the engineering function as headcount grows.

What you'll do

  • Build reinforcement learning environments from proprietary datasets.
  • Develop and deploy AI agents for business customers.
  • Help company leadership decide technical direction and plan what to build next.
  • Take on leadership of the engineering team as it expands.
  • Deliver quickly without lowering quality standards in a startup setting.

Requirements

What we're looking for

  • 3 to 7 years of engineering experience with strong reinforcement learning fundamentals.
  • Prior experience building reinforcement learning environments, at an RL-focused company or a data company with hands-on RL exposure.
  • Hands-on experience building and running AI agents in production.
  • Daily use of AI-assisted coding tools as part of production work.
  • Living in the Bay Area or ready to move there, with a full in-office schedule.

Bonus points

  • Prior experience at a leading human data company.
  • Full-stack engineering background, for example TypeScript and AWS.
  • Mobile development experience with iOS, Swift or React Native.
  • Startup experience with a demonstrated record of shipping quickly.

Benefits

Compensation and benefits

Base salary

USD 125,000 to 200,000 per year

  • Performance bonus

Location and work model

  • San Francisco, CA, United States
  • On-site
  • Full-time

Skills

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