Machine Learning Engineer

About this role

Sepal AI builds the world’s hardest AI benchmarks—grounded in real-world enterprise and operational systems. We work with experienced professionals to develop high-fidelity simulations and benchmarks that challenge the capabilities of frontier AI models. We’re hiring a Machine Learning Engineer to help us design and validate realistic ML evaluations. that reflect the complexity of enterprise-grade systems. You'll work on short-term engagements to solve applied ML problems, assess solution quality, and contribute to AI research by grounding benchmark tasks in practical, real-world use cases. RESPONSIBILITIES -Develop and validate machine learning solutions based on real-world enterprise problems -Translate ambiguous business goals into well-defined ML tasks and workflows -Evaluate data quality, model performance, and implementation feasibility -Document decisions, trade-offs, and key assumptions clearly and concisely -Collaborate asynchronously with internal teams to align on solution quality and technical expectations MINIMUM QUALIFICATIONS -English fluency -Legally eligible to work and located in the U.S. -Graduate degree (Master's or higher) in Computer Science, Data Science, Statistics, or a related field -Minimum of 5 years of professional experience in machine learning, data science, or applied analytics -Available for 10–20 hours per week -Reliable internet connection and access to a laptop or desktop computer -Comfortable using collaborative tools (e.g., Google Docs, GitHub, Slack, video conferencing) -Strong ability to work independently, manage time effectively, and follow written instructions EXPERIENCE QUALIFICATIONS -Demonstrated experience building ML models using real-world data in a production or enterprise setting -Skilled in Python and core ML/data libraries (e.g., pandas, scikit-learn, XGBoost, TensorFlow or similar) -Adept at assessing the strengths and limitations of ML approaches in business contexts -Experience working across a range of pro