[Remote] Machine Learning Engineer Expert
Note: The job is a remote job and is open to candidates in USA. Crossing Hurdles is seeking a Machine Learning Engineer Expert to build, evaluate, and improve real-world machine learning solutions on a flexible remote contract. The role involves developing end-to-end machine learning solutions, analyzing datasets, and improving model performance through systematic experimentation.
Responsibilities
- Develop end-to-end machine learning solutions for prediction and modeling problems
- Analyze datasets and choose appropriate modeling approaches, validation strategies, and metrics
- Perform exploratory data analysis, preprocessing, and feature engineering
- Train, tune, and evaluate models across tabular, text, image, and time-series datasets
- Build strong reference solutions using industry-standard ML techniques and best practices
- Review technical quality, document assumptions, and communicate results clearly
- Improve model performance through systematic experimentation and iteration
Skills
- Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university
- 2+ years of hands-on experience developing, training, evaluating, and optimizing ML models in a professional or research setting
- Strong Python skills and experience with tools such as scikit-learn, XGBoost, LightGBM, PyTorch, or TensorFlow
- Experience building complete ML workflows, from data preparation through validation and evaluation
- Strong understanding of evaluation metrics, validation methodologies, and experimental design
- Ability to work independently on open-ended technical problems and deliver high-quality outputs
- PhD from a leading research university
- Experience at technology companies, AI labs, research institutions, or high-growth startups
- Competitive ML/data science experience
- Experience with ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning
- Publications, patents, open-source contributions, or experience mentoring/reviewing ML work
Benefits
- Flexible schedule, with projects that may be extended, shortened, or concluded based on needs and performance.
- Weekly payments through Stripe or Wise based on services rendered.
Company Overview