Zanskar - Salt Lake City, UT
posted 3 days ago
About the position
The Machine Learning Scientist will play a critical role in accelerating our goals of rapid development of geothermal energy in the US. Although geothermal is abundant, there is extreme geographic variability in how accessible it is at shallow depths that are commercially viable. Finding a resource is a time and labor-intensive process of identifying targets, drilling exploration wells, and collecting other field data. This process requires significant upfront costs with highly uncertain outcomes. The Scientist's role will be to help Zanskar achieve its mission to augment, automate, and optimize these processes with custom AI tools and algorithms. Successful work will de-risk the process, discover resources that would remain hidden, and drive down development costs.
Responsibilities
- Develop, train, and evaluate models for tasks such as image recognition, object detection, spatial analytics, etc.
- Work with large-scale geospatial datasets, applying advanced techniques to extract meaningful insights.
- Design and implement web applications to facilitate data ingestion, data exploration and QC, automation tasks, and deployment of machine learning models.
- Leverage data science infrastructure (cloud compute, Github, Docker, CI/CD pipelines, SQL database, Terraform, etc.)
Requirements
- Minimum 5+ years experience in machine learning and/or data science in a business environment.
- Master's or Ph.D. in Computer Science, Machine Learning, Geostatistics, Geophysics, or similar preferred.
- Proven experience in developing and deploying machine learning models in a business setting, preferably with a focus on deep learning, geospatial applications, and/or computer vision.
- Proven experience developing and deploying dashboards and web applications in a business setting.
- Strong programming skills in Python and SQL and experience with machine learning libraries/frameworks (e.g., scikit-learn, PyTorch, and/or PyTorchLightning).
- A commitment to coding best practices (version control, peer review, documentation, CI/CD deployment, etc.).
- Familiarity with geospatial data formats, GIS tools, and geospatial libraries (GDAL, GeoPandas, etc.).
- Strong mathematical and statistics background.
Nice-to-haves
- Experience with Bayesian statistics and decision analysis theory.
Benefits
- Paid holidays
- 15 days PTO + PTO accrual increase based on tenure
- 3 days sick leave
- Medical, dental and vision coverage
- 401k
- Stock options
- Growth opportunities at a company with a direct impact in displacing carbon emissions
