Director of AI/ Machine Learning

LiquidPiston-posted 6 months ago
Full-time • Senior
Bloomfield, NJ
11-50 employees
Machinery Manufacturing
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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.

  • Lead the AI strategy by developing a comprehensive roadmap for applying machine learning to engine design, simulation, and testing.
  • Define data architecture and set up high-performance computing infrastructure.
  • Identify high-impact use cases for machine learning in engine design.
  • Build, refine, and validate both physical and data-driven models for systems such as engines, generators, hybrid power platforms, and UAVs.
  • Analyze simulation and experimental data to uncover insights and optimize system performance.
  • Recommend changes to mechanical or control systems based on findings.
  • Communicate results through formal reports and informal updates.
  • Collaborate closely with the engineering team and company leadership to prioritize initiatives and allocate resources.
  • Manage multiple R&D efforts, balancing immediate deliverables with long-term innovation.
  • Work hands-on with tools like Python, R, and MATLAB.
  • Oversee external technical partners as needed.
  • Ph.D. in Computer Science (or related) with a strong foundation in Data Science, Engineering, Physics, Mathematics, or Statistics.
  • Direct experience building and running Large Language Models (LLMs) - from IT infrastructure setup through training and deploying the models.
  • 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, training and fine-tuning models, and deploying models.
  • 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.
  • Experience setting up and deploying 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.
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