Physical AI Engineer

Intel Intel · Semiconductors · Shanghai, China

The Physical AI Engineer role at Intel focuses on designing and developing integrated AI solutions for deep learning and machine learning systems, encompassing hardware, software, firmware, and silicon. The role involves AI systems architecture, defining product specifications, and impacting the AI product roadmap. Key responsibilities include developing new methods in areas like reinforcement learning, computer vision, and robotics, leading design and implementation of AI systems, and delivering end-to-end technical solutions for customer problems. The role also involves analyzing AI infrastructure reliability and collaborating on next-generation requirements.

What you'd actually do

  1. Responsible for the overall design and development of integrated Artificial Intelligence (AI) solutions for deep learning and machine learning systems that integrate hardware, software, firmware, board, and silicon components with specific focus on customer requirements and implementation limitations throughout the systems lifecycle.
  2. Develops new methods in the areas of reinforcement learning, policy learning, computer vision, machine learning, simulation, sim2real, autonomous driving, and robotics.
  3. Leads design, analysis, and implementation of componentlevel choices across the integrated AI systems on performance, features, and cost, including analysis of risks and emphasis on ease of use, reliability, security, availability, maintainability, sustainability, and quality.
  4. Delivers endtoend technical solutions to solve customer problems, deploying solutions, executing benchmark tests, and preparing documentation.
  5. Conducts analysis and makes reliable engineering recommendations to ensure reliability/resiliency of the AI infrastructure.

Skills

Required

  • Python
  • PyTorch
  • TensorFlow
  • Jax
  • Linux
  • English

Nice to have

  • C++
  • Shell
  • system tuning
  • drivers/kernel basics
  • CUDA
  • TensorRT
  • memory management
  • Intel OpenVINO
  • ONNX Runtime
  • OpenCL
  • performance optimization
  • parallel computing
  • system profiling
  • compilers/toolchains
  • ROS/ROS2
  • robotic hardware debugging
  • Isaac Sim
  • MuJoCo
  • PyBullet
  • Robotics
  • Reinforcement Learning
  • Multimodal AI
  • Systems technology
  • Embodied AI
  • VLA
  • Multimodal learning
  • Computer Vision
  • Machine Learning
  • Simulation
  • sim2real
  • Autonomous Driving

What the JD emphasized

  • Master's, or PhD in Computer Science, Robotics, Artificial Intelligence, Automation, Electronic Engineering, or related majors.
  • Project and work experience related to robotics, reinforcement learning, multimodal AI, or systems technology.
  • Solid programming foundation, proficient in Python; familiarity with C++ is preferred.
  • Proficient in at least one deep learning framework: PyTorch, TensorFlow, or Jax.
  • Experience with projects or papers in directions such as Embodied AI, RL, VLA, or Multimodal learning is preferred.
  • Familiar with Linux operating systems; experience with Shell, system tuning, or drivers/kernel basics is preferred.
  • Experience with CUDA (e.g., kernel calls, TensorRT, memory management, etc.) is preferred.
  • Familiar with or willing to deeply learn inference frameworks such as Intel OpenVINO, ONNX Runtime, and OpenCL.
  • Experience in performance optimization, parallel computing, system profiling, or compilers/toolchains is a plus.
  • Experience with ROS / ROS2 or robotic hardware debugging is preferred.
  • Experience with simulation platforms such as Isaac Sim, MuJoCo, or PyBullet is preferred.

Other signals

  • Develops new methods in the areas of reinforcement learning, policy learning, computer vision, machine learning, simulation, sim2real, autonomous driving, and robotics.
  • Delivers end-to-end technical solutions to solve customer problems, deploying solutions, executing benchmark tests, and preparing documentation.
  • Contributes applied/customer knowledge to AI roadmap working with AI system architects.