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Opportunity

  • 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.
  • Experience employing workflow orchestration tools (Dagster, Airflow, Prefect, etc) or other techniques for coordinating complex operational machine learning and data processing pipelines.
  • 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.
  • 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.
  • 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.
  • Provide leadership in the architecture and implementation of core infrastructure underpinning the company’s ML weather forecast modeling pipelines for both research and operational applications.
  • On occasion, work with broader Product and Engineering teams to develop early proof-of-concept applications and demonstration products.
  • Establish 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.

Apply now