AI Applications Engineering Internship

AI Applications Engineering Intern

As a leader in next-generation geothermal, Fervo is building a dedicated AI team to unlock transformational value across drilling, reservoir modeling, operations, and commercial strategy. We are seeking a motivated PhD-level AI Applications Engineering Intern to contribute to cutting-edge applications of artificial intelligence in the clean energy sector.

This internship offers a unique opportunity to work on high-value applied research and development-ready AI tools that directly impact Fervo's ability to accelerate geothermal development. Projects may include:

• Designing hybrid AI-physics models for subsurface forecasting
• Developing machine learning algorithms for real-time drilling optimization
• Creating retrieval-augmented generation (RAG) systems for knowledge management
• Building predictive models for preventative maintenance and operational reliability
• Supporting commercial teams with power price forecasting and scenario modeling

The intern will report to Fervo's Strategy Team, serving as internal consultant to partner with end-user departments. This role offers a chance to apply advanced AI research to real-world challenges, guiding decision-makers through complex technical, operational, and commercial problems.

Responsibilities

• Develop, train, and evaluate advanced AI models (LLMs, ML, time-series, hybrid physics-informed)
• Collaborate with end-user teams to scope and deliver applied AI solutions
• Contribute to Fervo's centralized AI infrastructure and data architecture
• Document methodologies and provide clear technical communication to technical and non-technical stakeholders
• Present findings and recommendations to cross-functional teams, including senior leadership

Required Qualifications

• PhD candidate in Computer Science, Applied Mathematics, or a related quantitative field with a focus on AI/ML
• Strong proficiency in Python and machine learning frameworks (e.g., PyTorch, TensorFlow, Scikit-learn)
• Demonstrated research experience in one or more of: large language models, time-series analysis, physics-informed ML, optimization, or reinforcement learning
• Ability to apply theoretical knowledge to practical, messy, real-world datasets
• Excellent problem-solving, communication and collaboration skills
• Self-starter with the ability to scope and drive projects independently

Preferred Qualifications

• Experience with energy systems, industrial operations, or geoscience applications
• Prior experience with RAG architectures, data engineering, or scalable model deployment

Location

Fervo Energy has offices in Houston, TX, Golden, CO, Reno, NV, Oakland, CA, and Salt Lake City, UT. This position will be eligible for some hybrid work flexibility, but regular in-office presence at our Houston Office will be required.