Machine Learning Research Engineer, Model Evaluation

Responsibilities

• Evaluation strategy — Work with our Meteorology team to develop a rigorous, meteorologically valid strategy for comparing WeatherMesh with leading AI and physics-based models. Choose the metrics, datasets, baselines, and case studies that provide an honest picture of forecast quality.
• Fast feedback and durable systems — Build quick evaluations that give researchers useful signals, then turn recurring analyses into reliable, reusable infrastructure. Think systematically about reproducibility, provenance, and how evaluation tools fit into the broader research workflow.
• Agentic tooling for evals — Improve our existing evaluation infrastructure, including agentic AI-based tools for investigating forecasts and synthesizing results.
• Technical communication — Produce clear scorecards, visualizations, and explanations for researchers, leadership, customers, and external partners. Communicate model performance precisely, including uncertainty and important caveats.

Requirements

• Excellent scientific judgment and healthy skepticism. You ask whether a comparison is fair, what else could explain a result, and what evidence would change your mind.
• Strong experimental taste: you can identify the evaluation that answers the question that matters and distinguish robust improvement from noise.
• Systems thinking: you can solve today’s problem while recognizing what should become reusable infrastructure for future work.
• Experience evaluating ML systems using large, scientific, geospatial, multidimensional, or time-series datasets.
• Strong Python skills and experience with scientific and ML tools such as PyTorch, NumPy, pandas, or xarray.
• Able to investigate ambiguous results independently, synthesize evidence, and communicate conclusions clearly.
• Experience with weather, climate, forecasting, physical science, or AI-assisted research tools is helpful, but not required.

Benefits

• 401(k)
• Dental, health, and vision insurance
• Unlimited PTO
• Stock Option Plan
• Office food and beverages

Pay

$140k–$240k. We consider a range of backgrounds and experience levels and adjust offers to be competitive with market rates.

Schedule

Hybrid or in-person.