ML Engineering Intern - LLM Focus
Top Benefits
About the role
Company Introduction Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .
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
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
- For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
ML Engineering Intern - LLM Focus
Top Benefits
About the role
Company Introduction Mercor connects elite creative and technical talent with leading AI research labs. Headquartered in San Francisco, our investors include Benchmark , General Catalyst , Peter Thiel , Adam D'Angelo , Larry Summers , and Jack Dorsey .
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
- For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome/welcome
- For any help or support, reach out to: support@mercor.com
PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.