Machine Learning Staff Software Engineer, Pixel Camera

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.

The Google Pixel team focuses on designing and delivering the world's most helpful mobile experience. The team works on shaping the future of Pixel devices and services through some of the most advanced designs, techniques, products, and experiences in consumer electronics. This includes bringing together the best of Google’s artificial intelligence, software, and hardware to build global smartphones and create transformative experiences for users across the world.

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience with software design and architecture.
• Experience with C, C++, machine learning, and embedded systems.
• Experience with machine learning algorithms.
• Experience with machine learning architecture.
• Experience with machine learning research.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• Experience taking machine learning models from research prototype to production on mobile or embedded devices, and owning them after launch.
• Experience optimizing models for on-device accelerators through quantization, hardware-aware architecture design, or custom kernels.
• Experience building and training models in JAX/TensorFlow.

Responsibilities

• Design and implement the real-time on-device machine learning foundation that turns raw camera and sensor input into structured signals driving immediate application behavior.
• Drive the optimization of outlook models for NPU, GPU, and DSP execution, including quantization, hardware-aware architecture design, and custom kernel development, in partnership with the Tensor silicon and compiler teams.
• Own models end-to-end, from prototype through deployment on hundreds of millions of devices — training pipelines in JAX and TensorFlow, C++ integration into the camera pipeline, and long-term maintainability.
• Partner with product, UX, software, and hardware teams to define the requirements for next-generation interactive features, and translate roadmap goals into designs achievable within device constraints.
• Establish best practices for machine learning development, deployment, and evaluation. Define how model quality is measured; and contribute to the long-term technology roadmap.