Director of AI/ Machine Learning

LiquidPiston, Inc. is reimagining the rotary engine, and we’re building cutting-edge propulsion systems for next-generation power applications. We're now seeking a Director of AI/ Machine Learning to help us accelerate development and innovation across our advanced engine platforms. This is a unique opportunity to lead the integration of AI/ML into mechanical engineering and propulsion system design—from simulation and modeling to real-world performance optimization. You’ll work closely with the CEO and core engineering team in a fast-paced, hands-on R&D environment.

What You’ll Do
In this role, you will lead the AI strategy by developing a comprehensive roadmap for applying machine learning to engine design, simulation, and testing. This includes defining data architecture, setting up high-performance computing infrastructure, and identifying high-impact use cases. You'll build, refine, and validate both physical and data-driven models for systems such as engines, generators, hybrid power platforms, and UAVs. A key responsibility will be analyzing simulation and experimental data to uncover insights and optimize system performance. Based on these findings, you’ll recommend changes to mechanical or control systems and communicate results through formal reports and informal updates. You’ll collaborate closely with the engineering team and company leadership to prioritize initiatives, allocate resources, and adapt to evolving technical needs. Project management will be essential as you juggle multiple R&D efforts, balancing immediate deliverables with long-term innovation. You’ll work hands-on with tools like Python, R, and MATLAB, and you’ll also oversee external technical partners as needed. Above all, we value a proactive, solution-oriented mindset—someone who thrives in a fast-moving, creative, and collaborative environment.

Required Qualifications:

• Ph.D. in Computer Science (or related) with a strong foundation in Data Science, Engineering, Physics, Mathematics, or Statistics.
• Someone who has direct experience building and running Large Language Models (LLMs) — from IT infrastructure setup through training and deploying the models, as well as integrating them with agent-based systems.
• 3+ years of hands-on experience in AI, data science, or scientific computing, especially applied to physical systems.
• Deep understanding of numerical methods, optimization, and statistical analysis.
• Strong coding skills and comfort working in computational environments (Python is essential).
• Experience with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with Large Language Models (LLMs), including:
  • Setting up infrastructure (e.g., servers, containers, GPU clusters)
  • Training and fine-tuning models
  • Deploying models and building tools or agents that utilize them
• Solid grasp of physics and thermodynamics principles.
• Proven ability to build, validate, and optimize models of real-world systems.
• Self-starter who thrives on solving tough problems independently and creatively.
• Experience sourcing and learning from academic literature.

• Interest in engines (rotary, piston, or turbine), propulsion, or energy systems.
• Bonus if you’ve set up and deployed LLMs
• Experience setting up computing environments (Kubernetes, ZFS, Docker, license management, etc.).
• Familiarity with big data tools (AWS, Snowflake, Azure Data Lake).
• GUI development skills, or experience using AI to help build UI tools.
• Experience combining simulation results with experimental test data.
• Proposal writing or grant experience.
• Hands-on experience in a machine shop or prototype R&D setting.
• Familiarity with SolidWorks, ANSYS, GT Suite, or similar simulation/modeling software.