Remote ML Engineer Intern — RL/LLM Research & CI/CD

Feedinkoo; United States; Remote; USD 48,000 - 96,000; Part time

Job summary

Feedinkoo is seeking an ML Engineering Intern as a contractor, offering a remote, hourly position with a flexible schedule and about 35 hours per week. The role focuses on building CI/CD pipelines, containerized environments, and tooling to support agents interacting via CLI and APIs.

You will contribute to RL and LLM experiments while handling data collection and analysis. The ideal candidate balances engineering work with research and has hands-on experience with Docker, GitHub projects, and

Qualifications

• Background in machine learning, reinforcement learning or related coursework.
• Experience with LLM or RL projects or contributions.
• Proficiency with Docker, CLI tooling, and GitHub project management.
• Experience building integrations and managing data pipelines.
• Ability to balance engineering tasks with research activities.

Responsibilities

• Build and maintain CI/CD workflows for ML projects.
• Set up and manage containerized environments using Docker.
• Develop tooling to enable agents to interact via CLI and APIs.
• Support RL and LLM research experiments and prototypes.
• Handle data collection, preprocessing, and analysis.
• Collaborate asynchronously with research teams and adapt to changes.
• Document workflows and experimental results clearly and reproducibly.

Skills

Machine Learning

Reinforcement Learning

LLM Projects

Docker

CLI tooling

GitHub

Data Pipelines

Research Experience

Startup Environment

Team Collaboration

Education

ML coursework

Tools

Docker

CLI Tools

GitHub

CI/CD Pipelines

Data Pipelines

Job description

Feedinkoo is seeking an ML Engineering Intern as a contractor, offering a remote, hourly position with a flexible schedule and about 35 hours per week. The role focuses on building CI/CD pipelines, containerized environments, and tooling to support agents interacting via CLI and APIs.

You will contribute to RL and LLM experiments while handling data collection and analysis. The ideal candidate balances engineering work with research and has hands-on experience with Docker, GitHub projects, and