Machine Learning Software Engineer, Silicon

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; San Diego, CA, USA .

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
• 8 years of experience in software development, and with data structures/algorithms.
• 5 years of experience with design and architecture, and testing/launching software products.
• Experience with Machine Learning.

Preferred qualifications:

• PhD in Computer Science.
• Experience with embedded devices.
• Experience in running a large program or several projects simultaneously.
• Experience in building and shipping a programming framework or an SDK.
• Experience in computer architecture, in particular for accelerators such as an ML accelerator, GPU, or DSP.
• Knowledge of how a parallelizing optimizing ML compiler works.

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.

EdgeTPU is a family of embedded Machine Learning (ML) accelerators aiming towards a broad set of applications, from smartphones to self-driving cars to data center applications. We are developing a template design to aim the broad span of speed/energy dissipation/cost trade-offs corresponding to the many devices being developed. The Compute software team makes the Edge TPU ML accelerator programmable, via tooling that includes a compiler, runtime, SDK with documentation and further tooling, and an Applied ML team that optimizes ML models for serving on device.

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 $231,000-$339,000 + 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 for new hire 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

• Identify usability pain points for the EdgeTPU SDK, build a roadmap for new tools and features to improve overall usability for compiler, runtime API, tools and documentation. Extend the internal SDK for external Pixel developers.
• Lead a team of engineers on multiple sites and teams to triage customer issues, incorporating the learnings in the next generation of hardware, and making the software robust through scalable design.
• Improve processes around SDK release, qualification and communication with an emphasis on automation and monitoring.
• Help to decide which capabilities our hardware offering should accelerate. Identify trade-offs for flexibility versus performance to set the direction to hardware design.
• Enhance the current TPU programming model for advanced users. Design new mechanisms to support user-guided compilation to extract maximum performance out of the hardware.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.