Physical AI Engineer

Physical AI Engineer

We are building real-world Physical AI systems where models interact with physical machines. This role is for a robotics engineer with a strong reinforcement learning (RL) mindset someone who wants to train evaluate and deploy intelligent behaviors that emerge through interaction not just perception by building the virtual environments generating the data that trains our models and developing the policies that eventually run on real hardware.

Day to day you will design simulation environments produce large volumes of labeled synthetic data train and evaluate learned policies and work with engineers across robotics controls and perception to close the sim-to-real gap. You will work hands-on with NVIDIA Omniverse Isaac Sim physics-based simulation and foundation models. This is a builder role: fast iteration scalable training and direct transfer from simulation to physical robots.

• Build and maintain high-fidelity physics-accurate simulation environments in NVIDIA Omniverse and Isaac Sim for training testing and validating robotic systems.

• Generate synthetic datasets at scale including sensor and camera simulation domain randomization procedural scene variation and automated annotation such as segmentation depth bounding boxes and pose. You own dataset quality versioning and delivery.

• Design and run reinforcement learning and imitation learning pipelines using simulation-generated and synthetic data.

• Train and tune policies for control planning navigation and manipulation with emphasis on robustness and sim-to-real performance.

• Define task curricula reward functions and evaluation benchmarks so policy performance is measured before it reaches hardware.

• Model sensors actuators and contact behavior and debug simulation instability non-physical behavior and determinism issues.

• Drive simulation-to-real transfer through domain randomization system identification and validation on physical systems.

• Build reusable tooling APIs and documentation so the broader team can stand up new environments and tasks without deep simulation expertise.

• Integrate foundation models to support reasoning task decomposition and human-in-the-loop learning.

• 5 years in robotics reinforcement learning simulation or applied machine learning. Degree in Robotics Computer Science or a related field or equivalent hands-on experience.

• Hands-on experience training robotic agents in simulation on physical systems or both.

• Strong background in reinforcement learning imitation learning or learning-based control including domain randomization and curriculum learning.

• Proven experience building simulation environments in NVIDIA Omniverse Isaac Sim or Isaac Lab or comparable GPU-accelerated simulation platforms.

• Direct experience generating synthetic data for model training including sensor simulation annotation pipelines and large-scale dataset generation.

• Working knowledge of OpenUSD as a robotics engineer including asset conversion into a simulation pipeline from formats such as URDF or MJCF.

• Production experience with at least one RL library: RSL-RL RL-Games skrl or Stable-Baselines3.

• Strong Python and the deep learning stack such as PyTorch or JAX with the ability to build and scale training pipelines beyond a single workstation.

• Experience applying or integrating foundation models into robotics or decision-making workflows.

• Builder mindset with a track record of moving learning systems from experiment to deployment.

• PhysX schemas and physics tuning.

• MuJoCo Playground NVIDIA Warp or Newton.

• Omniverse Replicator or comparable synthetic data generation frameworks.

• World foundation models used for data augmentation and photoreal domain transfer.

• Vision language action models or multimodal policies.

• ROS 2 or comparable robotics middleware real-time systems or physics engines.

• Model-free or model-based RL at scale including distributed or cloud-scale training orchestration.

• Training perception models such as detection segmentation or pose estimation on synthetic data.

• C alongside Python for real-time robotics systems.

• Experience operationalizing learned policies on physical robots in production environments.

• Remote or hybrid US-based with periodic time onsite at our robotics facility.

• Occasional domestic and global travel.

• Flexible working hours aligned to experimentation and training cycles.

--- This description is optimized to attract senior handson AI robotics engineers with strong reinforcement learning and simulation expertise.

At TD SYNNEX our values guide everything we do: Together We Own It We Dare to Go We Grow and Win and above all We Do the Right Thing. These principles shape how we work with each other our partners and our communities as we drive innovation and create lasting impact.

Whats In It For You

• Elective Benefits: Our programs are tailored to your country to best accommodate your lifestyle.
• Grow Your Career: Accelerate your path to success (and keep up with the future) with formal programs on leadership and professional development and many more on-demand courses.
• Elevate Your Personal Well-Being: Boost your financial physical and mental well-being through seminars events and our global Life Empowerment Assistance Program.
• Diversity Equity & Inclusion: Its not just a phrase to us; valuing every voice is how we succeed. Join us in celebrating our global diversity through inclusive education meaningful peer-to-peer conversations and equitable growth and development opportunities.
• Make the Most of our Global Organization: Network with other new co-workers within your first 30 days through our onboarding program.
• Connect with Your Community: Participate in internal peer-led inclusive communities and activities including business resource groups local volunteering events and more environmental and social initiatives.

Dont meet every single requirement Apply anyway.

At TD SYNNEX were proud to be recognized as a great place to work and a leader in the promotion and practice of diversity equity and inclusion. If youre excited about working for our company and believe youre a good fit for this role we encourage you to apply. You may be exactly the person were looking for!

We are an equal opportunity employer and committed to building a team that represents and empowers a variety of backgrounds perspectives and skills. All qualified applicants will receive consideration for employment without regard to race color religion national origin gender gender identity or expression sexual orientation protected veteran status disability genetics age or any other characteristic protected by law.

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