Job Description
The Senior Machine Learning Scientist will develop advanced AI models and decision-making systems to improve geothermal resource exploration and development, working closely with geoscientists and engineers to emulate physics-based simulations and optimize drilling strategies.
Key Responsibilities
- Build fast, reliable models that emulate or augment physics-based simulations such as reservoir and wellbore workflows
- Evaluate and compare multiple modeling approaches, including physics-informed models, operator learning, transformers, and diffusion models
- Develop multi-step decision systems for exploration and appraisal using POMDP-style planning and belief-space decision making
- Translate scientific and engineering questions into well-defined learning and decision problems with specific inputs, outputs, constraints, and success metrics
- Prototype, benchmark, and iterate across decision-making approaches like POMDP solvers, reinforcement learning, VOI baselines, and MPC, then harden into workflows and APIs
- Collaborate with geoscientists, reservoir engineers, and software engineers to integrate models and policies into production software
Requirements
- Three years of applied machine learning experience, ideally in scientific ML, decision-making under uncertainty, surrogate modeling, robotics control, or related engineering science domains.
- Expertise in Python and modern ML tooling, with PyTorch preferred.
- Track record of taking models from prototype through rigorous evaluation to adoption by technical stakeholders.
- Strong fundamentals in probability and statistics, and comfort working with messy, real-world scientific datasets.
- Experience building or using surrogate models for expensive simulators, PDE-driven systems, multi-physics, or similar systems.
- Proficiency in surrogate modeling, sequential decision-making under uncertainty, and reinforcement learning.
- Software engineering skills including Git, code review, reproducibility, CI basics, and Docker container workflows.
- Experience with diffusion models.
- Exposure to subsurface modeling domains such as geothermal, oil and gas, CCS, hydrogeology, or related geoscience fields.
- Familiarity with cloud infrastructure and data systems including SQL, object storage, and orchestration.
Benefits & Perks
Paid holidays
15 days PTO with accrual increase based on tenure
Medical, dental and vision coverage
401k
Stock options
Growth opportunities at a company with a direct impact in displacing carbon emissions
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