Machine Learning Engineer | Upstream Tech | Remote
Upstream Tech is a technology company that builds software products to accelerate the pace, scale and impact of conservation, restoration and a renewable grid. We are looking for a backend engineer who is excited to grow and improve state-of-the-art water forecasting systems to address clean energy, environmental conservation and climate adaptation challenges.
We are hiring a Machine Learning Engineer to join the team scaling HydroForecast. HydroForecast helps clean energy and environmental water users proactively prepare for and manage water in an increasingly variable climate. HydroForecast was recently proven to be the most accurate river forecast available and we are rapidly expanding to support increased interest.
Working with the HydroForecast team you will some or all of the following:
- Design and build machine learning models to forecast water supply.
- Setup and evaluate production models, tracking performance and devising strategies to improve them.
- Incorporate science and physics into model design and function
- Scale the operational data processing and machine learning inference systems producing our forecasts.
- Investigate and integrate new weather, water, snow and other geospatial data sources to provide to our customers and models.
- Optimize data processing and machine learning systems to enable rapid experimentation and deployment of new models.
- Improve automated alerting, observability and testing of operational forecast systems.
- Hone developer systems and processes to make the team more productive.
This work is critical to the success of Upstream Tech and our environmental mission. Our climate and conservation impact scales with our team & systems.