Sepal AI builds rigorous, high-stakes evaluation environments to test the limits of modern AI systems. They are looking for an experienced ML / DS practitioner to help design and vet challenging predictive tasks and automated workflows in their datasets and agent evaluations.
Requirements
- Strong working knowledge of clustering, time-series forecasting, classification, and other applied modeling approaches
- Fluency in Python and core ML libraries like pandas, scikit-learn, xgboost, prophet, etc.
Responsibilities
- Evaluate and refine complex ML tasks (identify corner cases, clarify specs, and guide the design of predictive pipelines) that are grounded in business logic and real-world data.
- Build net new modeling pipelines.
- Ensure integrity across existing pipelines (data ingestion, feature extraction, training, and evaluation), especially for edge cases and failure modes.
Other
- 3+ years experience working as a Data Scientist, or ML Engineer (Early looking for individuals with enterprise experience rather than research or academic.)
- Strong attention to detail and high standards for correctness and clarity
- Fully remote
- Flexible hours (ideally 30–40 hrs/week)
- Duration: 2–4 months to start, with potential for extension
