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: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Design and develop robust software for real-time robotic workloads, including RTOS tuning and memory management.
- Build and maintain CI/CD infrastructure and hardware-in-the-loop (HIL) testbenches to support rapid development cycles.
- Establish systems, tools, and processes for high-velocity robot development, including logging and data visualization.
- Ensure low-latency communication and system stability across the entire robot stack.
- Establish a culture of following software development best practices, including modularity, well documented code, and high test coverage.
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 5 years of experience developing and debugging robotic software systems and supporting toolchains.
- 3 years of experience testing, maintaining, or launching core components of a robotics software stack, and 1 year of experience with software design and architecture of a robotics software stack.
- 3 years of experience with processor and memory optimization, real-time operating systems (RTOS), and communication protocols (e.g., CAN, SPI, I2C, UART).
Preferred qualifications:
- Experience with GPU/TPU optimization for model inference and sensor fusion.
- Experience with system simulation tools such as Mujoco, NVIDIA Isaac Sim, or Gazebo.
- Knowledge of robotic system design, including kinematics, dynamics, control algorithms, and perception systems.
- Ability to deliver high-quality and durable software with appropriate test coverage.
- Insights into how safety impacts system design across physical and software layers.