Opportunity
- Be one of the initial hires at a remote startup, started by experienced entrepreneurs, developing a transformative approach to AI earth system modeling.
- Build the world’s best weather forecast and data analysis system using a data-driven, end-to-end learned approach.
- 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 building data pipelines for weather or remote sensing data, and 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.
- Experience employing workflow orchestration tools (Dagster, Airflow, Prefect, etc) or other techniques for coordinating complex operational machine learning and data processing pipelines.
- Experience coordinating software and developer tooling across research and engineering teams.
- Demonstrated technical leadership and experience developing and deploying infrastructure to support MLOps at scale.
- Ability to work independently.
- Flexibility and adaptability to work on diverse projects and pivot when necessary.
Great to Have
- Experience working as a technical leader in a research-focused startup and/or similar unit within a larger technical organization, emphasizing rapid R&D and subsequent operationalization of new technologies.
- Passion for using the latest AI-assisted coding and development tools to solve hard engineering problems.
- Experience working closely with research scientists / engineers and supporting the development of tools and processes to aid ML R&D, as a machine learning engineer or other similar role.
- Familiarity with weather data, numerical weather prediction models, or machine learning weather models.
Responsibilities
- Establish and maintain best practices and workflows for software and data engineering across the company’s development portfolio.
- Provide leadership in the architecture and implementation of core infrastructure underpinning the company’s acquisition of diverse weather and climate data, including model datasets and satellite observations.
- Collaborate with the founding team to push the boundaries of observation-driven ML for weather forecasting.