Zanskar Geothermal & Minerals, Inc

Title: Machine Learning Engineer - Geospatial AI. The Machine Learning Engineer 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.. Algorithm Development: Design and implement geospatial machine learning algorithms tailored for geospatial data analysis and forecasting. Experienced intersection of ML & Geospatial programming: Master's or Ph. D. in Computer Science, Machine Learning, Geostatistics, Geophysics, or any other Earth science or engineering discipline that leverages statistics, machine learning and/or high performance computing.. Strong collaborator: The AI team interacts closely with geoscientists, land leasing, project finance, field technicians, and others to make sure the tools they build create real impact on development decisions.

machine learning engineer

<div><div>Role Overview Title: Machine Learning Engineer - Geospatial AI Hours: Full time Location: Salt Lake City, UT (Hybrid, Remote possible) Pay: $140k $210k Benefits Eligible: Yes Manager: Ognjen Grujic - Head of Machine Learning Our Mission Geothermal energy is the most abundant 24/7 renewable energy source in the world. There is 2,300 times more energy in geothermal heat in the ground than in oil, gas, coal, and methane combined. However, historically it s been hard to find and expensive to develop. At Zanskar, we re using AI to better find and develop new geothermal resources in order to make geothermal a cheap and vital contributor to a carbon-free electrical grid. Zanskar has raised >$15M from top-tier VC firms and is planning for significant growth over the next 12 months. The Machine Learning Engineer 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 Engineer 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. Problems you ll solve The geological factors that make our work difficult and interesting are temperature and depth heterogeneity resulting largely from differences in the underlying source of heat (e.g., magmatism, radioactivity) as well as the processes of heat transfer (e.g., conductive, convective) and where those favorably intersect other commercial factors like access to the grid. In for first six months, you will refine and develop apps & algorithms using various datasets to unlock our ability to predict geothermal potential including: <ul><li>Algorithm Development: Design and implement geospatial machine learning algorithms tailored for geospatial data analysis and forecasting</li><li>Model Training and Evaluation: Develop, train, and evaluate models for geospatial tasks such as image recognition, object detection, spatial analytics, etc</li><li>Geospatial Data Processing: Work with large-scale geospatial datasets, applying advanced techniques to extract meaningful insights</li><li>Infrastructure: Build and/or maintain our ML infrastructure (cloud compute, Github, CI/CD pipelines, SQL database management, etc.) </li></ul>What we re looking for <ul><li>Experienced intersection of ML & Geospatial programming: Master's or Ph.D. in Computer Science, Machine Learning, Geostatistics, Geophysics, or any other Earth science or engineering discipline that leverages statistics, machine learning and/or high performance computing. Skills include:</li><li>Proven experience in developing and deploying machine learning models, preferably with a focus on geospatial applications (i.e. satellite data analysis) or computer vision</li><li>Familiarity with geospatial data formats, GIS tools, and geospatial libraries (GDAL, GeoPandas, etc.)</li><li>Strong programming skills in Python and SQL, and experience with machine learning libraries/frameworks (i.e. sklearn, PyTorch and/or PyTorchLightning)</li><li>Strong collaborator: The AI team interacts closely with geoscientists, land leasing, project finance, field technicians, and others to make sure the tools they build create real impact on development decisions. The Engineer must be able to translate business requirements into technical solutions and communicate/collaborate with a variety of stakeholders</li><li>Intrinsically motivated: Zanskar is a team of mission-oriented professionals who live by the value Blaze a Trail, Leave a Legacy. We work on problems no one else has solved before, so we need curious self-starters with a strong penchant for solving complex ML problems </li></ul>Location, Salary, and Benefits <ul><li>The position is located in Salt Lake City, UT</li><li>Full time, Base salary range $140k $210k</li><li>Paid holidays, and 15 days PTO/sick leave</li><li>Medical and dental coverage</li><li>A direct impact in displacing carbon emissions, and growth opportunities in a growing startup environment </li></ul>Equal Opportunity Employer Zanskar is an equal-opportunity employer and complies with all applicable federal, state, and local fair employment practice laws.</div></div>#J-18808-Ljbffr Associated topics: .net, algorithm, back end, c++, develop, developer, python, software developer, software programmer, sw

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