Applications Engineer – Hybrid Machines
Phillips Corporation
AI Applications Engineering Intern
Fervo Energy
internship
Posted on:
Location: 🇺🇸 United States
Visit company websiteJob Level
Entry Level
Tech Stack
JavaScriptPythonPyTorchSaltStackScikit-LearnTensorflow
About the role
- 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
- Report to Fervo’s Strategy Team and serve as internal consultant to partner with end-user departments
- Work on projects such as subsurface forecasting, real-time drilling optimization, RAG systems, predictive maintenance, and power price forecasting
Requirements
- PhD candidate in Computer Science, Applied Mathematics, or 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: Experience with energy systems, industrial operations, or geoscience applications
- Preferred: Prior experience with RAG architectures, data engineering, or scalable model deployment
