Machine Learning Engineer Expert

Mercor is seeking experienced Machine Learning Engineers and Applied Machine Learning Researchers to design, solve, and evaluate complex machine learning challenges that reflect real-world ML workflows.

This role requires strong hands-on modeling expertise, experience building end-to-end machine learning solutions, and deep familiarity with modern machine learning techniques across multiple data modalities and problem domains.

Contributors will help develop high-quality reference solutions and evaluate technical quality across machine learning projects used to improve advanced AI systems.

What You'll Do

Build End-to-End Machine Learning Solutions

• Develop machine learning solutions for complex prediction and modeling problems
• Analyze datasets and determine appropriate:
  • Modeling approaches
  • Validation strategies
  • Evaluation metrics

Data Analysis & Preparation

• Perform exploratory data analysis (EDA)
• Conduct feature engineering
• Build preprocessing pipelines
• Prepare datasets for modeling and experimentation

Model Development

• Train, tune, and evaluate models across:

  • Tabular datasets
  • Natural language datasets
  • Image datasets
  • Time-series datasets

• Apply industry-standard machine learning techniques and best practices

Quality Review & Evaluation

• Review machine learning projects and deliverables
• Validate technical correctness and methodology
• Document:
  • Assumptions
  • Methodologies
  • Evaluation results
  • Experimental findings

Model Optimization

• Improve model performance through:
  • Iterative experimentation
  • Hyperparameter optimization
  • Evaluation and analysis

Required Qualifications

Education

• Master's degree or PhD in:
  • Computer Science
  • Machine Learning
  • Statistics
  • Mathematics
  • Electrical Engineering
  • Related quantitative disciplines

Experience

• 2+ years of hands-on machine learning experience in:
  • Industry
  • Research
  • Applied ML environments

Technical Skills

• Strong Python proficiency

• Experience with frameworks such as:

  • scikit-learn
  • XGBoost
  • LightGBM
  • PyTorch
  • TensorFlow

• Experience building complete machine learning pipelines including:

  • Data preparation
  • Feature engineering
  • Model development
  • Validation
  • Evaluation

Domain Expertise

Experience in one or more of:

• Tabular machine learning
• Natural language processing
• Computer vision
• Recommendation systems
• Ranking systems
• Time-series forecasting

Additional Requirements

• Strong understanding of:

  • Evaluation metrics
  • Validation methodologies
  • Experimental design

• Ability to work independently on open-ended machine learning problems

Preferred Qualifications

• PhD from a leading research university

• Experience at:

  • Technology companies
  • AI labs
  • Research institutions
  • High-growth startups

• Participation in machine learning competitions

• Experience optimizing models against performance-based metrics

• Familiarity with:

  • Ensembling
  • Hyperparameter optimization
  • Transfer learning
  • Foundation model fine-tuning
  • Reinforcement learning

• Publications, patents, or significant open-source contributions

• Experience mentoring, reviewing, or evaluating machine learning practitioners

Compensation

• $90/hour
• Weekly payments through Stripe or Wise

Contract & Payment Terms

• Independent contractor engagement
• Fully remote work
• Flexible schedule
• Projects may be extended, shortened, or concluded based on project needs and performance

Important Note

Mercor currently cannot support:

• H1-B candidates
• STEM OPT candidates

About Mercor

Mercor partners with leading AI labs and enterprises to train and improve frontier AI systems using human expertise.

Contributors work alongside researchers and experts helping shape the next generation of AI technologies.