Machine Learning Engineer
Rainmaker
Software Engineering
El Segundo, CA, USA
Posted on Jan 17, 2025
Rainmaker is pioneering a modern cloud seeding system to solve water scarcity and inclement weather problems. We develop and incorporate radar validation, weather-resistant UAS, numerical weather modeling, and sustainable cloud seeds into an effective precipitation enhancement solution.
The Engineering team at Rainmaker works on our UAS, dispersion payload, and in-situ/remote sensing systems. If you are interested in working in an extremely innovative and fast paced environment, where your work directly makes an impact and difference in our operational system, this is a fantastic opportunity.
We're creating the first scalable solution for enhancing rainfall using precision cloud seeding. Our technology combines real-time weather data, automated ground stations, and aerial operations to increase precipitation where it's needed most. We're seeking our first Machine Learning Engineer to build the infrastructure and systems that make precision weather modification possible.
Why We're Here
Water scarcity threatens billions. At Rainmaker, we don't just predict the weather - we modify it. You'll build ML systems that detect optimal seeding conditions, guide autonomous aircraft through storms, and prove exactly how much rain we create. Working with meteorologists, you'll transform atmospheric science into realtime systems that do what humans have dreamed of for millennia: make rain fall from the sky.
What You'll Do
- Design ML systems to predict optimal seeding conditions by fusing radar, satellite, and ground sensor data in realtime
- Develop autonomous guidance systems that navigate aircraft to precise positions in complex weather systems
- Build validation systems that quantify exactly how much additional precipitation we create
- Construct robust data pipelines that integrate our ground radar network with public weather data sources
- Work directly with meteorologists to incorporate physical constraints and validate predictions against meteorological theory
- Deploy and optimize models for icing detection on a UAV
Required Qualifications
- MS/PhD in Machine Learning, Computer Science, or related field, or equivalent experience
- Strong track record building production ML systems with demonstrable impact
- Deep expertise in spatial-temporal data processing and realtime prediction
- Extensive experience with PyTorch or TensorFlow and ML deployment pipelines
- Proven ability to handle complex sensor fusion and noisy environmental data
- Experience optimizing models for resource-constrained environments
- Strong foundation in physics and enthusiasm for learning atmospheric science
- Clear communication skills and ability to collaborate with domain experts
Preferred Qualifications
- Background in meteorology, atmospheric science, fluid dynamics, or other physical sciences
- Experience processing weather radar or satellite imagery
- Track record of incorporating physical constraints into ML models
- Familiarity with autonomous systems or robotics
- Experience deploying ML to edge devices
How to Apply
Along with your resume, share specific examples of your most impactful technical work - published research, open source projects, or novel solutions you've built. We're seeking work that pushed boundaries and created lasting impact.
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