Machine Learning Performance Engineer

Jobinhalt

Google welcomes people with disabilities.

Due to the current health crisis related to COVID-19 and the escalating visa/travel restrictions in place, we’re currently unable to extend offers to anyone who cannot work from Taiwan due to lockdown visa/travel restrictions, or other restrictive measures until further notice. Consequently, we will be prioritizing candidates who can start in this location by set date as expected. We’re keeping the situation under review and would adjust our position should the restrictive measures be removed later on.

Minimum qualifications:

• Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent practical experience.
• 5 years of relevant work experience in computer performance.
• Experience with one or more general purpose programming languages including but not limited to: C/C++ or Python.
• Educational experience or working experience in Machine Learning or image processing.

Preferred qualifications:

• Master’s or PhD degree in Computer Science or Electrical Engineering.
• Experience with deep learning frameworks including TensorFlow and full-stack software.
• Experience with ASIC architecture.
• Proven track record optimizing/architecting software/hardware solutions for machine Learning, image processing, power and performance analysis.
• Strong track record of outreach to Machine Learning researchers and application developers.

About The Job

Our computational challenges are so big, complex and unique we can’t just purchase off-the-shelf hardware, we’ve got to make it ourselves. Your team designs and builds the hardware, software and networking technologies that power all of Google’s services. As a Hardware Engineer, you design and build the systems that are the heart of the world’s largest and most powerful computing infrastructure. You develop from the lowest levels of circuit design to large system design and see those systems all the way through to high volume manufacturing. Your work has the potential to shape the machinery that goes into our cutting-edge data centers affecting millions of Google users.

In this role, you will work on enabling the leadership machine learning workload performance on a heterogeneous compute platform and architecture. With the knowledge in Neural Network models, you will participate heavily in the hardware architecture and contribute to the driver, runtime, and API strategy and innovations.

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.

Responsibilities

• Work with a team of hardware and software engineers to build infrastructure to optimize machine learning workloads on a heterogeneous platform.
• Develop, implement, and maintain infrastructure needed for effective machine learning workload analysis and performance/power improvement on the platform.
• Work collaboratively with full stack software engineers to partition machine learning workload to select compute engines to enhance user experiences.
• Collaborate with hardware architects to evolve future machine learning heterogeneous compute architecture and develop tools and flows.

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 this form .