Platform AI Robotics Engineer III — Edge & Production

HCL Technologies Limited; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

HCL Technologies Limited is seeking a Physical AI Engineer (Robotics & Agentic Systems) to build and deploy Physical AI solutions on Google stack, integrating DeepMind Robotics models with Gemini foundation models to create autonomous agents. You will move from simulation (MuJoCo-Warp) to production hardware at scale.

You will work with Intrinsic Flowstate, ROS 2, Python, and JAX/Optax, deploying skills across robotic arms and sensors while optimizing performance on TPUs and GPUs.

Qualifications

• Experience integrating AI models with robotics on edge/hardware platforms.
• Ability to deploy embodied reasoning models to robotic systems.
• Familiarity with simulation-to-production workflows and high-fidelity environments.

Responsibilities

• Model Integration: Deploy Gemini Robotics-ER models to enable robots to understand natural language and physical causality.
• Workflow Orchestration: Build agentic workflows connecting cloud-based reasoning with edge execution.
• Simulation & Training: Run high-fidelity simulations to generate data for edge robotics.
• Hardware Abstraction: Develop hardware-agnostic robotic skill implementations for multiple arms/sensors.
• System Optimization: Use JAX/Flax/Optax for efficient computations on TPUs/GPUs.

Skills

Robotics

Edge AI

Python

Problem solving

Tools

Intrinsic Flowstate

ROS 2

MuJoCo-Warp

JAX

XLA

Orbax

G4 VMs

NVIDIA Blackwell

Job description

HCL Technologies Limited is seeking a Physical AI Engineer (Robotics & Agentic Systems) to build and deploy Physical AI solutions on Google stack, integrating DeepMind Robotics models with Gemini foundation models to create autonomous agents. You will move from simulation (MuJoCo-Warp) to production hardware at scale.

You will work with Intrinsic Flowstate, ROS 2, Python, and JAX/Optax, deploying skills across robotic arms and sensors while optimizing performance on TPUs and GPUs.