Open roles

Geospatial Data Engineer

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 and data analysis system using a data-driven, end-to-end learned approach.
Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.

BS, or MS in computer science, mathematics, applied statistics, machine learning, physics, meteorology, geography, or equivalent industry experience.
3+ years of industry experience developing peta-scale data infrastructure, ideally working with a multitude of geospatial data from weather/climate models, satellites, radar, and types of observation systems.
Expert proficiency in Python.
Practical experience working with diverse weather/environmental data formats, including HDF5, NetCDF, Tiff/GeoTiff, BUFR, GRIB, and various weather radar formats.
Experience and proficiency working with systems and tools designed for large-scale data processing and archival, including Parquet, Apache Beam/Google Cloud Dataflow, BigQuery, or equivalent systems and tools on AWS or Azure.
Experience designing, rapidly prototyping, and evaluating complex data processing systems
Proficiency in communicating system designs to and with input from technical stakeholders including scientists and engineers.
Ability to work independently.
Flexibility and adaptability to work on diverse projects and pivot when necessary.

Knowledge about weather and climate observation systems and data, especially from satellite platforms.
Familiarity with NOAA/NASA/ESA/JAXA satellite data and other datasets commonly leveraged for numerical weather prediction and data assimilation applications.
Familiarity developing in Fortran, C++.
Familiarity with common open-source tools developed in the world of weather/climate for interacting with legacy data, including eccodes package from ECMWF and the various NCEPLIBS-* from NOAA.
Experience collaborating or working with stakeholders from diverse communities, including academic researchers and civil servants working at NOAA or similar agencies.
Hands-on experience designing and building applications on Google Cloud Platform leveraging managed services/products.
Expertise in designing data systems which feed into large-scale AI/ML model training and inference.

Collaborate with the founding team to advance the state of the art in weather forecasting using a data-driven, end-to-end learned approach.
Design and implement peta-scale data processing systems for building AI/ML-ready datasets core to the company’s scientific research and product portfolio.
Work closely with the research team to design and generate datasets for AI/ML modeling.
Help develop and implement standards and frameworks for creating AI/ML-ready weather/climate observational datasets, and use these to publish datasets developed as part of the company’s scientific research agenda.
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.

Be one of the initial hires at a remote startup, started by experienced entrepreneurs, developing a transformative approach to earth system modeling.
Provide the world’s best weather forecasting tools to weather companies and companies, academia and governments making weather and climate related decisions
Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.

Bachelor’s degree or equivalent practical experience.
3+ years of Product Management experience in a technical domain (or something similar)
Experience creating product roadmap to launch, driving product vision, defining the GTM strategy, and leading design discussions.
Familiarity with AI products
Excellent communication and collaboration skills across technical and non-technical teams.
Data-driven mindset with a passion for using data to inform product decisions.
Ability to work at startup speed, action orientation
Ability to work independently.
Sense of humo(u)r

Experience working in weather or climate, and with applications across industries such as energy, transportation, and finance.
Understanding of machine learning’s applications in weather forecasting.
Familiarity with API and developer tool products.
Passion for open science and the positive impact of technology on society.
Knowledge of multiple functional areas such as Product Management, Engineering, UX/UI, Sales, Customer Support, Finance or Marketing.

Collaborate with the founding team to define the product vision and roadmap.
Understand the target market segments and their specific needs for weather and climate forecasting and tools
Distill capabilities and opportunities into clear, actionable product requirements.

Prioritize features based on market needs, user impact, and technical feasibility.
Manage the product roadmap, ensuring on-time and on-budget delivery.
Champion the customer experience, and deliver delight

Prioritize target customer segments, help develop design partners and initial customers
Collaborate with marketing to develop product launch strategy and messaging, user acquisition, and product adoption plans.
Track key product metrics and measure success against defined goals.

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 a data-driven, end-to-end learned approach.
Join a multi-disciplinary team committed to open science and sharing results with the broader weather and climate communities.

BS, MS, or PhD in computer science, mathematics, applied statistics, machine learning, physics, or equivalent industry experience.
Practical experience in applying experimental ideas to real-world problems.
Strong understanding of machine learning and statistical methods.
Experience with Python-based ML frameworks such as PyTorch or JAX.
Proficiency in running, tracking, and analyzing experiments, with the ability to instrument them with meaningful metrics and visualizations.
Strong troubleshooting skills to diagnose and resolve issues in machine learning workflows.
Ability to work independently.
Flexibility and adaptability to work on diverse projects and pivot when necessary.

Expertise in developing and optimizing data loaders for various storage solutions.
Experience with distributed, multi-node training for machine learning models.
Proficiency with software environment management tools such as conda or Docker.
Familiarity with ML architectures such as Graph Neural Networks (GNNs), transformers, and diffusion models.
Experience working with physical sensor data.
Familiarity with the basic principles of numerical weather prediction systems.

Collaborate with the founding team to advance the state of the art in weather forecasting using a data-driven, end-to-end learned approach.
Identify and prototype promising ML approaches from the broader research community
Conduct experiments, analyze results, and scale up approaches that demonstrate experimental success.
Establish best practices and workflows for distributed training to ensure efficient and effective scaling of machine learning models.
Collaborate with our data engineering team to create efficient and maintainable data loading pipelines for a wide range of sensor data.
Promote engineering and research best practices by conducting code reviews and ensuring high-quality code.