Scientific / ML Engineer

Mercor; United States; Remote; USD 130,000 - 195,000; Part time

Job summary

Mercor seeks researchers to join its GenAI team, driving cutting-edge development of large language models and related ML systems. You will guide cross-disciplinary teams, design complex ML tasks, and produce runnable reference solutions.

The role emphasizes performance evaluation, rigorous data pipelines, and reproducible results. The ideal candidate has 4+ years in ML/data science or scientific computing, with strong Python expertise and a track record of publications or open-source

Qualifications

• 4+ years of dedicated professional or research experience in ML, data science or scientific computing at a top-tier org or university.
• Proficiency with PyTorch, JAX or TensorFlow and strong Python (NumPy, Pandas, scikit-learn).
• Publications/open-source contributions or shipped ML systems are a strong plus.

Responsibilities

• Join a leading AI lab's GenAI team and contribute to advanced LLM development.
• Guide research and engineering teams to improve AI model performance.
• Design and implement challenging ML tasks with runnable reference solutions.
• Evaluate ML tasks and provide clear technical feedback.
• Develop rubrics to assess methodology, correctness and reproducibility.
• Collaborate with SME to ensure data quality and consistency.

Skills

Strong Python (NumPy, Pandas, scikit‑L

Publications/Open‑source contributions

Career progression demonstrated

Education

MS in a quantitative field

PhD in a quantitative field

Tools

PyTorch

JAX

TensorFlow

Job description

Responsibilities

Join a leading AI lab's cutting-edge GenAI team to be at the core of the AI revolution, where your expertise fuels the development of the most advanced Large Language Models.

Guide research and engineering teams to close knowledge gaps and improve AI model performance in machine learning and scientific computing, model training and evaluation, and numerical and scientific software topics.

Design challenging, domain-relevant tasks, and write accurate and well-structured solutions to machine learning and scientific computing problems.

Evaluate machine learning and scientific computing tasks and solutions and provide clear, written technical feedback.

Design and evaluate technical tasks covering model training, experiment design, data pipelines and scientific simulations, with runnable reference solutions.

Develop rubrics to assess the methodological soundness, correctness and reproducibility of ML and scientific work.

Collaborate with other subject matter experts to ensure consistency and accuracy in training data.

Requirements

4+ years of dedicated professional or research experience in machine learning, data science or scientific computing at a recognized, top-tier organization or research university (an MS or PhD in a quantitative field counts toward this).

Production or research experience with PyTorch, JAX or TensorFlow, and strong Python (NumPy, pandas, scikit-learn).

Publications, open-source contributions or shipped ML systems are a strong plus.

Demonstrable career progression.

Ability to engage reliably for at least 20 hours/week during weekdays.

Strong written communication skills and the ability to explain complex technical decisions clearly.