Software Engineer, Imaging and Multimedia System, Silicon

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in C/C++, and with data structures/algorithms.
  
• 3 years of experience working with embedded operating systems for mobile SoCs, and 1 year of experience with software design and architecture.
  
• 3 years of experience in system software development including kernel and user mode drivers, HAL, and multimedia subsystems (Camera ISP, Video, GPU, and Display).
  

Preferred qualifications:

• Experience with system architecture analysis for complex imaging and multimedia user experiences to identify performance and power bottlenecks.
  
• Experience collaborating with teams/stakeholders to launch features and use-cases on mobile devices.
  
• Experience in software development with Python or Java.
  
• Experience with ML inference pipeline development and optimization.
  
• Experience with graphics processing unit and digital signal processing software development for imaging, computer vision and multimedia applications using programming languages (e.g., OpenCL, Vulkan, CUDA, Halide and architecture specific C/C++ intrinsics)
  
• Experience with mobile SoC architecture and multimedia subsystems (Camera ISP, TPU/NPU, GPU, Video Codecs, Display Engine and Security)
  

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.

In this role, you will build Google Tensor, System-on-Chip (SoC) that powers the latest Pixel phones. You will productize the latest Machine Learning (ML) innovations and research by delivering computing hardware and software.

Google's mission is to organize the world's information and make it universally accessible and useful. Our team combines the best of Google AI, Software, and Hardware to create radically helpful experiences. We research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful. We aim to make people's lives better through technology.

The US base salary range for this full-time position is $161,000-$239,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Responsibilities

• Contribute to imaging and multimedia systems architecture and design for Google’s Tensor SoCs and Pixel devices.
  
• Build prototype/production software across the Android camera and multimedia stack including kernel and user mode drivers, HAL and framework, Machine Learning (ML) stack, and application to prove feasibility of new and emerging use-cases on future Tensor SoCs.
  
• Collaborate with multimedia IP and architecture, system architecture and device software teams to take the prototypes into production.
  
• Perform detailed system analysis for complex imaging and multimedia user experiences to identify performance and power bottlenecks and areas for optimizations, and communicate the analysis results in both quantitative and qualitative fashion.