About the role#
This internship offers a 12-week project where you drive your own work from start to finish. You will work alongside teams building geothermal energy technology to solve business problems. At the end of the summer, you will present your findings to executive leadership and department heads. You will act as an internal consultant, partnering with various departments to address technical, operational, and commercial challenges.
What you'll do#
- Develop, train, and evaluate advanced AI models, including LLMs, ML, and hybrid physics-informed models.
- Collaborate with end-user teams to scope and deliver applied AI solutions.
- Contribute to centralized AI infrastructure and data architecture.
- Document your methodologies and provide technical communication to stakeholders.
- Present findings and recommendations to cross-functional teams and leadership.
What you'll need#
- Graduate student or PhD candidate in Computer Science, Applied Mathematics, or a related quantitative field.
- Strong proficiency in Python and machine learning frameworks like PyTorch, TensorFlow, or Scikit-learn.
- Demonstrated research experience in LLMs, time-series analysis, physics-informed ML, optimization, or reinforcement learning.
- Ability to apply theoretical knowledge to practical, real-world datasets.
- Experience with energy systems, industrial operations, or geoscience applications is a plus.
- Familiarity with RAG architectures, data engineering, or scalable model deployment is preferred.
Location & details#
- Location: Houston, Texas
- Term: Summer 2027
- Work Modality: On-site
- This is a full-time, paid internship.
About Fervo Energy
Fervo Energy develops geothermal power projects to provide carbon-free energy. The company uses drilling and subsurface analytics to make geothermal power cost competitive. Founded in 2017, it operates as a privately held business. The team consists of over 300 employees based in Houston and Berkeley.
How to get in at Fervo Energy
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