Machine Learning Engineer Job at Google, Mountain View, CA

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Job Description

Minimum qualifications:

  • Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience.
  • 8 years of experience in product management, consulting, co-founder, or a related technical role.
  • 3 years of experience building and shipping technical products.
  • Experience with machine learning related silicon including specialized machine learning accelerators, DSP, GPU, CPU.

Preferred qualifications:

  • Master's degree, PhD, or a related field.
  • Experience defining and launching silicon products for consumer hardware.
  • Knowledge of computing and software frameworks/tools and software development life cycles for machine learning solutions.
  • Excellent communication and people management skills.

About the job

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 $164,000-$252,000 + 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.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.


Responsibilities

  • Define custom machine learning hardware that brings to life key experiences around productivity, health and fitness, entertainment, social connection, etc. and distinguish our first-party devices by delivering experiences with end user impact.
  • Work cross-functionally to assess and select challenges to overcome through custom silicon, build multi-year roadmaps that intersect our long term device strategy, and secure executive support for new machine learning hardware.
  • Ensure machine learning hardware has a clear path to productization, and drive internal stakeholders and partner engagements necessary for the on-time launch of the product.
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.

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