Research Engineer
Bio & Science AIonsite
At a glance
Highlights
- Build the world's best weather forecast with end-to-end learned modeling.
- Own projects spanning research and production forecasting systems.
- Advance earth system modeling and share results via open science.
Ideal candidate
Adaptable ML researcher who thrives with autonomy and owns complex projects end-to-end. Excited by weather, open science, and turning prototypes into real customer forecasts.
Requirements
- MS or PhD in computer science, mathematics, machine learning, physics, atmospheric science, or equivalent industry experience
- Strong understanding of machine learning and statistical methods
- Proficiency in deep learning frameworks like PyTorch, JAX, or TensorFlow
- Proficiency running, analyzing, and troubleshooting ML experiments and workflows
- Track record driving technically complex projects from start to finish
- Flexibility to work on diverse projects and pivot when necessary
- Positive, solutions-focused approach to technical challenges
- 3+ years of industry experience
- Hands-on experience with GNNs, transformers, and diffusion models
- Background applying deep learning to spatiotemporal systems like weather or fluids
- Experience with physical sensor data
- Experience with distributed, multi-node training
- Familiarity with numerical weather prediction and data assimilation
- Strong software engineering fundamentals for ML and modular pipelines
- Experience improving ML systems used by real customers
- remote policy
- remote-first
Lab profile
About Brightband
Developing data-driven AI models to build the world's best weather forecast.
What they build
- AI weather forecasting system
- AI earth system models
- Weather data analysis tools
Known for
- End-to-end learned modeling
- Data-driven forecasting approach
- Open science focus
- Remote-first multidisciplinary team
Key facts
- Remote-first startup
- Early-stage startup
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