Machine Learning Research Engineer

Responsibilities

• AI-based data assimilation — Develop methods for incorporating real-time observations from balloons, satellites, weather stations, and other sources into our forecasts.
• A foundation model for weather — Work toward a single model capable of predicting many weather-related datasets, including variables and data products not covered by traditional global forecasts.
• Messy, large weather datasets — Find, understand, clean, and combine large datasets with inconsistent formats, resolutions, coverage, and quality. Determine which data is actually useful and build systems that make it easier to use again.
• Rapid experiments — Test ideas quickly, learn from failures, and follow promising results into the weeds and chase down another 1% of model improvement.
• Infrastructure and systems — Turn successful experiments into reusable systems that accelerate future research.
• Research direction — Form hypotheses, design convincing experiments, keep up with relevant ML research, and help decide which ideas are worth pursuing.
• Whatever the problem needs — Venture into operations, infrastructure, evaluation, data engineering, or other technical side quests when needed to get the research working in practice.

Qualifications

• Strong research taste: you can identify important questions, design experiments that answer them, and recognize when a result is real.
• Deep enthusiasm for machine learning and a desire to understand models in detail rather than treating them as black boxes.
• Strong Python and PyTorch skills, with experience developing and debugging nontrivial ML systems.
• Experience working with large, messy datasets and building dependable pipelines or abstractions around them.
• Able to iterate quickly while thinking systematically about which work should become durable infrastructure.
• Comfortable crossing boundaries between research and engineering and learning unfamiliar tools or domains as needed.
• Experience with weather, climate, geospatial data, scientific machine learning, computer vision, or time-series forecasting 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.