Be one of the initial hires at a remote startup, started by experienced entrepreneurs, developing a transformative approach to earth system modeling.
Build the world’s best weather forecast using an approach that learns directly from observational data.
Join a multi-disciplinary team that balances open science development with sustainably building commercial applications for novel weather forecasting tools and approaches .
Requirements
5+ years of industry experience in software engineering, working on a diverse range of products, systems, and applications including operationalizing ML models and their supporting data infrastructure.
Expert proficiency in Python.
Hands-on experience designing and building cloud-native applications and infrastructure, leveraging managed services on Google Cloud Platform or Amazon Web Services.
Demonstrated success in conceptualizing and building user-facing products including web applications leveraging data from operational machine learning inference systems.
Experience designing and building user-facing APIs for distributing large geospatial datsets.
Ability to work independently.
Flexibility and adaptability to work on diverse projects and pivot when necessary.
Great to Have
Experience working in a research-focused startup and/or similar unit within a larger technical organization, emphasizing rapid prototyping and iteration on candidate products.
Experience working closely with research scientists, engineers, domain experts, and business to leaders to help execute on an early-stage startup’s product roadmap.
Familiarity with weather data, numerical weather prediction models, or machine learning weather models.
Familiarity working with geospatial data at scale, including weather/climate datasets, remote sensing data, and other forms of weather observaitons.
Familiarity with developing and implementing APIs for interacting with ML model inference systems and/or outputs.
Responsibilities
Collaborate with the founding team to push the boundaries of observation-driven ML weather forecasting.
Work closely with the Product, Science, and Engineering teams to scope and plan requirements for key product milestones and capabilities.
Provide leadership in building the initial iterations of the company’s core product suite, as well as coordination with key stakeholders across the company’s business units to rapidly prototype and deploy capabilities.
Contribute to best practices and workflows for data engineering across the company’s development portfolio.
Promote engineering best practices by conducting code reviews and ensuring high-quality code.