Role overview

Machine Learning Engineer

Requirements and responsibilities

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Role Responsibilities

  • Guide research and engineering teams to close knowledge gaps in AI and data science domains. Surface nuances that distinguish expert-level work from surface-level reasoning.
  • Design challenging agentic tasks rooted in real-world ML, data science, data engineering, and software workflows. Write accurate, well-documented solutions that serve as ground truth.
  • Evaluate AI agent outputs against your solutions. Provide detailed written feedback capturing correctness, efficiency, and reasoning quality.
  • Develop and refine evaluation frameworks and rubrics for assessing agentic behavior on AI and data science tasks.
  • Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

QualificationsMust-Have

  • 3+ years of research, academic, or industry experience in Machine Learning, Data Science, Software Engineering, Computer Science, Statistics, Biology, Electrical/Mechanical/Civil Engineering, Physics, Chemistry, Mathematics, Materials Science, or other STEM background.
  • Demonstrated technical expertise in programming, data analysis, ML modeling, statistical methods, or computational methods.
  • Ability to commit to 40 hours per week during weekdays for the duration of the engagement.
  • Strong written communication skills and the ability to explain technical decisions clearly.

Preferred

  • Prior experience with data annotation, labeling, evaluation, or human feedback collection.
  • Experience with LLMs, AI systems, or agentic workflows; familiarity with agentic frameworks.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: [email protected]
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