[Remote] Remote | Applied Machine Learning Evaluation Consultant — Up to $100/hour

Note: The job is a remote job and is open to candidates in USA. 24-MAG LLC is offering a specialized part-time consulting opportunity for experienced Machine Learning Engineers and Applied ML Researchers. The role involves developing end-to-end machine learning solutions, conducting dataset analysis, and providing technical evaluation and documentation for complex machine learning challenges.

Responsibilities

• Develop complete 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, data preprocessing, model training, tuning, and evaluation
• Work across tabular, text, image, time-series, recommendation, ranking, or other applied ML problem types
• Develop strong reference solutions using industry-standard machine learning techniques and best practices
• Document methodologies, assumptions, modeling choices, validation approaches, and evaluation results clearly
• Ensure solutions are accurate, reproducible, and technically well-structured
• Identify opportunities to improve model performance through systematic experimentation and iteration
• Review and validate the technical quality of machine learning projects and deliverables
• Evaluate modeling choices, data preparation decisions, performance metrics, and experimental design
• Identify weak assumptions, data leakage risks, flawed validation, underdeveloped features, or unsupported modeling conclusions
• Provide clear written technical feedback that improves correctness, rigor, and reproducibility

Skills

• Master's degree, PhD, or equivalent advanced experience in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field
• 2+ years of hands-on experience developing, training, evaluating, and optimizing machine learning models in a professional or research setting
• Strong proficiency in Python and modern machine learning frameworks such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow
• Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation
• Strong understanding of model evaluation metrics, validation methodologies, and experimental design
• Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs
• PhD from a leading research university
• Experience at leading technology companies, AI-focused teams, research institutions, or high-growth startups
• Participation in competitive machine learning or data science competitions
• Experience optimizing models against performance-based evaluation metrics
• Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning
• Publications, patents, or significant open-source contributions in machine learning or AI
• Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners

Benefits

• Fully remote with flexible scheduling
• Weekly payments via Stripe or Wise

Company Overview