Opportunity
- Be one of the first hires at a remote-first startup founded by experienced entrepreneurs and developing a transformative approach to earth system modeling.
- Build the world’s best weather forecast using a data-driven, end-to-end learned approach.
- Work with high autonomy in a fast-paced environment, owning projects that span both research and production systems.
- Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.
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 in running, analyzing, and troubleshooting ML experiments and workflows.
- Track record of driving technically complex projects from start to finish.
- Flexibility and adaptability to work on diverse projects and pivot when necessary.
- A positive, solutions-focused approach to tackling technical challenges.
Great to Have
- 3+ years of industry experience
- Hands-on experience with ML architectures such as graph neural networks, transformers, and diffusion models.
- A background in applying deep learning to spatiotemporal systems (weather, fluids, etc.).
- Experience working with physical sensor data.
- Experience with distributed, multi-node training of ML models.
- Familiarity with the basic principles of numerical weather prediction and data assimilation.
- Strong software engineering fundamentals for ML: writing maintainable, scalable code, and designing modular ML pipelines.
- Experience improving ML systems used by real customers or end-users.
Responsibilities
- Identify and prototype promising ML approaches from the broader research community.
- Conduct experiments, analyze results, and scale up approaches that demonstrate experimental success.
- Iteratively improve the models that power our production forecasts, ensuring high-quality outputs for customers.
- Promote engineering and research best practices by conducting code reviews and ensuring high-quality code.
- Collaborate with a small, focused team to advance the state of the art in weather forecasting using a data-driven, end-to-end learned approach.