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Machine Learning Engineer

At Raydar · India

Salary: US$50,000–150,000 a year

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Posted
19 October 2026
First seen by us
20 October 2026
Last checked
18 hours ago

Job description

From Raydar’s job post, as they wrote it.

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.

Read the full description

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.

Requirements

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.

Benefits

Compensation and benefits

- Base salary: USD 50,000 to 150,000 per year

Location and work model

- Remote (India)

- Full-time

Apply on Raydar (opens in a new tab)

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