Machine Learning Engineer
Raydar
Machine Learning Engineer
Raydar
AI-powered recruiting agency for tech roles
Raydar · India (Remote) · Full-time · Posted 2026-10-19
Salary: USD 50,000–150,000
Workplace: remote
About the company
Our client is a fast-growing technology company.
The role
Raydar is recruiting for this role on behalf of our client. Join a very small engineering team as an early hire, creating training environments for machine learning systems and shipping production AI agents. You will work side by side with company leadership on technical direction and are expected to step into leading engineering as the team expands.
What you'll do
- Build high-quality reinforcement learning environments for coding tasks from proprietary datasets.
- Develop and deploy AI agents for business customers.
- Partner with company leadership on technical direction and the roadmap.
- Lead the engineering team as it grows.
- Ship quickly and to a high standard in a fast-paced startup setting.
What we're looking for
- 3 to 7 years of engineering experience with strong reinforcement learning fundamentals.
- Practical experience applying reinforcement learning to coding problems.
- A track record of designing simulated training setups for learning systems, ideally in an AI research or data-labeling setting.
- Experience taking autonomous AI agents live in a production setting.
- Daily use of AI coding assistants as part of production work.
- Based in India, with willingness to work a 5.5-day week with overlap with Pacific time.
Bonus points
- Prior experience at a leading data-labeling company.
- Full-stack engineering background, for example TypeScript and AWS.
- Mobile app development experience, such as iOS, Swift or React Native.
- Prior startup experience with a clear record of shipping.
Compensation and benefits
- Base salary: USD 50,000 to 150,000 per year
Location and work model
- Remote (India)
- Full-time
Powered by Workable
Raydar is an AI-powered talent acquisition firm that serves tech-focused organizations on a contingency basis, charging client companies only after a successful hire. It uses proprietary AI to identify a large pool of candidates and conducts a short 15-minute AI-driven interview (recorded and transcribed) before human recruiters review materials, provide interview prep, and assist with offers and negotiations. What sets it apart is the blend of automated sourcing and screening with hands-on human oversight and tailored client support. Its goal is to help organizations hire more efficiently by speeding up sourcing while maintaining thorough evaluation and negotiation assistance.
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