Note: The job is a remote job and is open to candidates in USA. The University of Louisville is seeking a Senior AI Engineer to research and build Physical AI systems that enable autonomous sensing, decision-making, and action in the real world. The role develops and deploys computer vision, foundation models, robotics, edge computing, and cyber-physical systems across healthcare, defense, agriculture, and industrial applications.
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
Skills
- Master's degree or higher in Computer Engineering, Computer Science, or Data Science and 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
- 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
- Advanced computer vision & foundation models
- Self-supervised learning
- World models & robotics (sim-to-real)
- Edge AI & on-device inference
- Multimodal sensor fusion
- Cyber-physical & distributed (fleet) systems
- Cybersecurity & secure handling of sensitive data
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