Senior Software Engineer, Generative AI, Physical AI, Robotics

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in the C++ or Python programming language.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).
• Experience with modern robotics frameworks, kinematic motion planning, actuator control, and sensor integration.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• 5 years of experience with data structures and algorithms.
• Experience with Vision-Language-Action (VLA) foundation models, imitation learning, reinforcement learning, or LLM-based autonomous agent planning.
• Experience with MuJoCo, Isaac Sim/Gym, or PyBullet for motion retargeting, trajectory optimization, or policy training.
• Experience with bimanual manipulation, dexterous hands/grippers, mobile manipulators, or legged/humanoid kinematics.
• Experience interfacing software with real hardware, embedded communication protocols (CAN, UART, Ethernet), and automated testbeds.

About the job:

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

Our mission is to build an Embodied AI Agent to mimic human interaction with XR devices.

The next revolution in consumer computing is spatial—smart glasses and extended reality (XR) headsets that seamlessly integrate digital intelligence into our everyday physical world. But evaluating how smart glasses perform in the messy, unpredictable real world presents a massive engineering challenge: today, validation requires human operators to manually wear, tap, speak to, and walk around with devices.

We are building an autonomous Physical AI Agent designed to mimic human behavior, perception, and physical interaction with XR devices. Imagine an intelligent agent embodied in robotic hardware that can: don, adjust, and wear smart glasses with human-like dexterity; interact physically and conversationally—swiping capacitive touchpads, clicking tactile buttons, viewing visual displays, and conversing naturally with on-device multimodal AI assistants; and navigate real-world environments—walking, turning, and exploring rooms to rigorously evaluate spatial tracking, SLAM, and augmented reality visual stability without human intervention.

For decades, the computing revolution has reshaped our world driven by breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.

Responsibilities:

• Build robust, low-latency C++ and Python software pipelines for robotic motion planning, trajectory tracking, and multi-sensor feedback loops.
• Deploy robotic arms and Vision-Language-Action (VLA) foundation models to autonomously wear, adjust, tap, and interact with smart glasses.
• Emulate human sight, speech, and hearing to validate real-time conversational and visual interactions with multimodal AI assistants.
• Leverage mobile and kinematic robotic platforms and use modern physics simulators (e.g., MuJoCo, Isaac Sim) to model human kinematics, retarget recorded human motions to robotic bodies, and train robust policies before physical execution.
• Build agentic harnesses that translate natural language user journeys into synchronized physical execution across automated testbed fleets.