Senior Product Manager, Robotics Security, DeepMind

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in product management or a related technical role.

• 5 years of experience taking technical products from initial concept to launch.

Preferred qualifications:

• Experience in AI security, model defense, anti-distillation techniques, adversarial ML, red teaming, and securing physical AI ecosystems like robotics, drones, and autonomous vehicles.

• Expertise securing systems across hardware, firmware, operating systems, and software, combined with AI/ML fundamentals, cybersecurity, threat modeling, edge computing, and model security.

• Exceptional leadership driving complex, multi-year strategic bets, cross-functional initiatives while also simplifying complex technical concepts for senior executives while defining quantitative evaluation security metrics.

About the job:

At Google, we put our users first. The world is always changing, so we need Product Managers who are continuously adapting and excited to work on products that affect millions of people every day.

In this role, you will work cross-functionally to guide products from conception to launch by connecting the technical and business worlds. You can break down complex problems into steps that drive product development.

One of the many reasons Google consistently brings innovative, world-changing products to market is because of the collaborative work we do in Product Management. Our team works closely with creative engineers, designers, marketers, etc. to help design and develop technologies that improve access to the world's information. We're responsible for guiding products throughout the execution cycle, focusing specifically on analyzing, positioning, packaging, promoting, and tailoring our solutions to our users.

This is a leadership opportunity at Google DeepMind to own the product strategy for Robotics Security and Anti-Distillation. As autonomous robots and frontier models become more capable, they introduce new security challenges across physical execution and model protection. You will set the multi-year outlook to ensure our embodied AI systems remain safe, aligned, and resilient against attacks.

In this role, you will be the single-threaded product owner responsible for addressing threats like model extraction, unauthorized distillation, and adversarial attacks. Your scope includes defining the product roadmap for operationalizing anti-distillation defenses to safeguard proprietary IP, while establishing architectures that ensure system integrity.

You will navigate complex trade-offs between physical capability, autonomous execution velocity, and robust IP protection, aligning executive leadership across Google to deploy trustworthy, theft-resistant robotic and AI systems.

Artificial intelligence will be one of humanity’s most transformative inventions. At Google DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $256000 - $278000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google. Responsibilities:

• Define and own the multi-year outlook, strategy, and product roadmap for a portfolio of Robotics Security and Anti-Distillation initiatives across Google DeepMind.

• Lead product definition to build secure execution foundations and defend against threats like input manipulation, command injection, unauthorized distillation, and adversarial misuse.

• Translate research breakthroughs—such as watermarking, abuse detection, and query analysis—into scalable production defenses, ensuring frontier models and embodied agents remain secure.

• Partner closely with PhD Researchers, Engineering, Safety, and Legal teams to manage the complete product lifecycle from ambiguous research to large-scale strategic deployment.

• Drive alignment with senior leadership, establish defense efficacy metrics, and serve as the leading product authority bridging embodied AI research and production security.