Machine Learning Engineer Expert (Remote) at Mercor 2026

About the Job

We are seeking experienced Machine Learning Engineers and Applied ML Researchers to design, solve, and evaluate complex machine learning challenges that reflect real-world ML workflows. This role requires strong hands-on modeling expertise, the ability to develop high-quality reference solutions, and deep familiarity with modern machine learning techniques across a variety of domains and data modalities.

Job Overview

Position: Machine Learning Engineer Expert

Compensations: $90 / hour

Type: Hourly Contract, Fully Remote (Flexible Schedule)

Hiring Organization: Mercor

What You’ll Do

• Develop end-to-end machine learning solutions for challenging prediction and modeling problems.
• Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics.
• Perform exploratory data analysis, feature engineering, and data preprocessing.
• Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets.
• Develop strong reference solutions using industry-standard machine learning techniques and best practices.
• Review and validate the technical quality of machine learning projects and deliverables.
• Document methodologies, assumptions, and evaluation results in a clear and reproducible manner.

Required Qualifications

• Education: Master’s degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university.
• Experience: 2+ years of hands-on experience developing, training, evaluating, and optimizing machine learning models in a professional or research setting.
• Technical Skills: Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow).
• Domain Expertise: Demonstrated experience in one or more areas such as Tabular ML, NLP, Computer Vision, Recommendation/Ranking systems, or Time-series forecasting.

Preferred Qualifications

• PhD from a leading research university.
• Experience at leading technology companies, AI labs, research institutions, or high-growth startups.
• Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning.

Contract & Payment Terms

• Fully remote role that can be completed on your own schedule.
• Payments are processed weekly via Stripe or Wise.
• Please note: H1-B or STEM OPT candidates cannot be supported at this time.

How to Apply

Ready to help shape the next generation of AI systems? 👉 Apply Now for the Machine Learning Engineer Expert Position

💡 Expert Advice for Applicants

To fast-track your application through Mercor's evaluation process, keep the following insider tips in mind:

• Nail the MLE Assessment: Because this role requires high-level reference solutions, your upcoming Machine Learning Engineer assessment is critical. Be prepared to quickly write clean, production-grade Python code and demonstrate a flawless grasp of data preprocessing, cross-validation strategies, and model evaluation metrics.
• Highlight End-to-End Ownership: In your resume, focus on projects where you didn't just train a model, but actually owned the process from raw data engineering down to the metric evaluation and iterative optimization.
• Be Modality Versatile: While specialization is great, this role spans multiple data types. Ensure your portfolio or resume highlights your adaptability across different data structures (e.g., shifting from tabular XGBoost models to fine-tuning text or vision foundation models).
• Document Like a Researcher: Mercor values clear technical communication. When writing code or reference solutions, treat your documentation with the same rigor you would a research paper—clearly state your validation methodologies, assumptions, and baseline comparisons.