Senior AI Engineer – Physical

University of Louisville
$123,870 - $185,857Onsite

About The Position

The University of Louisville is seeking to hire a Senior AI Engineer to research and build Physical AI systems that move intelligence from isolated servers into the real world, systems that sense, understand, decide, and act autonomously. The role translates frontier AI into deployable systems across clinical imaging pipelines, autonomous robotics, and cyber-physical infrastructure, combining advanced computer vision and foundation/world models with robotics and edge computing. Highest-impact application areas include medical & healthcare, government & defense, and industry & agriculture, wherever real-time, autonomous physical execution is critical.

Requirements

  • Master’s degree or higher in Computer Engineering, Computer Science, or Data Science
  • Two (2) years of relevant experience.
  • At least 2 years of direct, hands-on experience in physical AI, robotics, or embodied AI, computer vision, robotics, and/or edge/embedded deployment (i.e., 2+ years working in this specific role).
  • Demonstrated expertise in computer vision and deep learning.
  • Hands-on experience with robotics and/or embedded/edge computing, with strong programming skills (e.g., Python) and modern ML frameworks.
  • Proven ability to work in secure environments that handle sensitive, confidential data, with a strong focus on cybersecurity. Must follow institutional security, privacy, and compliance controls (e.g., HIPAA, NIST 800-53) and apply secure engineering practices to protect sensitive data.

Nice To Haves

  • Foundation models and self-supervised learning; medical imaging (CT/WSI).
  • Robotics middleware (e.g., ROS), physics simulation, and sim-to-real transfer.
  • Edge/embedded deployment, multimodal sensor fusion, and UAV/autonomous platforms.
  • Record of open-source contributions and peer-reviewed publications.

Responsibilities

  • Develop advanced computer-vision and foundation models, including self-supervised learning that learns from raw, unstructured data and adapts rapidly to high-stakes, domain-specific tasks (e.g., medical imaging, defect detection).
  • Build world-model and robotics systems that develop an intuitive understanding of physics and space, enabling robots to anticipate outcomes, adapt in unpredictable environments, and transfer from simulation to reality.
  • Engineer cyber-physical and distributed systems: on-device (edge) inference for instant reflexes without connectivity, multimodal sensor fusion (camera, thermal, radar), and fleet intelligence that shares learning across devices.
  • Deploy AI onto edge hardware, drones, mobile robots, and sensor networks, for real-time autonomous data collection and action.
  • Apply the Sense → Understand → Decide → Act pipeline to concrete deployments in healthcare imaging/monitoring, defense, and precision agriculture/industry.
  • Produce open-source tools, testbeds, and peer-reviewed research.
  • Work within secure environments that handle sensitive data: apply cybersecurity best practices and institutional security and compliance controls (e.g., HIPAA, NIST 800-53) across every system built and operated.
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