Machine Learning Engineer | $90/hr

Codefeast; India; Remote; INR 9,723,000 - 13,848,000; Part time

Job summary

Codefeast is seeking experienced machine learning/AI researchers and simulation specialists for a remote contractor role. You will design and test scenarios for reinforcement learning agents, configure environments, and define agent interactions to validate behavior and improve the platform.

This position emphasizes hands-on RL work and clear feedback in a remote interview setting. Ideal candidates have hands-on experience with simulations, RL environments, and the ability to articulate workflow

Qualifications

• Professional experience in machine learning or AI research.
• Hands-on experience building simulations or reinforcement learning environments.
• Familiarity with platform configuration and reward structures.
• Comfortable sharing technical feedback in a remote interview.

Responsibilities

• Build and test scenarios for reinforcement learning agents.
• Configure environments and define agent interactions.
• Validate initial behavior and provide feedback on usability.

Skills

Machine learning / AI research

Reinforcement learning frameworks

Tools

RL frameworks

Job description

Experience: Professional machine learning or AI research experience required

Job Type: Contractor

Location: Remote

Compensation: $90/hour

Required Profiles: LinkedIn profile

Role Overview

We're seeking machine learning engineers, AI researchers, and simulation specialists to build and test scenarios for reinforcement learning agents. You'll configure environments, define agent interactions, validate initial behavior, and share feedback on the platform's usability.

Key Responsibilities

• Configure environment parameters and agent interaction rules.
• Describe your workflow and identify opportunities to improve the platform.

Key Requirements

• Professional experience in machine learning or AI research.
• Hands-on experience building simulations or reinforcement learning environments.
• Familiarity with platform configuration and reward structures.
• Comfortable sharing technical feedback in a remote interview.

Preferred Technical Skills

• Reinforcement learning frameworks and environments.
• Scenario and reward structure configuration.