ML Engineering Intern – LLM Focus at Mercor

Job Description

Role Overview

Position: Machine Learning Contractor (LLMs, RL, and Infrastructure) – Contract, Remote
Commitment: ~35 hours/week
Engage in research and engineering tasks focused on LLMs, RL, and infrastructure for advanced agent systems.

Responsibilities

Build and maintain GitHub-based project infrastructure, including CI/CD workflows.
Set up and manage environments with Docker and containerized services.
Develop and integrate coding tool environments for agents using CLI and APIs.
Contribute to reinforcement learning and LLM research experiments and prototypes.
Handle data collection, preprocessing, and analytics for ML projects.
Collaborate asynchronously with researchers and adapt to evolving project requirements.
Document infrastructure, pipelines, and experimental results clearly and reproducibly.

Requirements / Qualifications

Must-Have Qualifications

Background in machine learning, reinforcement learning, or related coursework.
At least 1–2 LLM or RL-related projects (e.g., shared on GitHub).
Proficiency with Docker, CLI tooling, and GitHub project management.
Experience building integrations and working with data pipelines/analytics.
Comfortable with both engineering-heavy and research-oriented tasks.

Preferred Qualifications

Ability to navigate ambiguous requirements in fast-moving environments.
Prior team or research lab experience is a strong plus.

Engagement Details

Remote and flexible, with optional monthly visits to the Mercor SF office.
Project-based, with potential for extensions based on research needs.
Competitive hourly compensation ($35-$70 range), payments issued weekly via Stripe Connect.
Contractors classified as independent freelancers.

Application Process (Takes 20-30 mins to complete)

Submit your resume and links to relevant project work (e.g., GitHub repositories, Docker setups).
Follow-up steps may include a technical assessment or project-based evaluation.
Typical response time: within a few days of application.

Resources & Support

PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.

Desired Skills and Experience
Python, TensorFlow, PyTorch, Reinforcement Learning, Large Language Models, Data Engineering, Infrastructure Management, Research Skills, Problem Solving, Collaboration