Minimum qualifications:
Bachelor's degree or equivalent practical experience.
3 years of experience in Machine Learning or Artificial Intelligence.

Preferred qualifications:
Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
3 years of experience with machine learning algorithms and tools (e.g. TensorFlow), artificial intelligence, deep learning, and/or natural language processing.
Publications or research experience in deep learning.
Experience with computer architecture, accelerator architecture design, power and performance analysis.
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.

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 in a team of hardware and software engineers to build tools for large-scale Auto Machine Learning (ML).
Design, build, and maintain infrastructure modules needed for automating customization and training of neural networks. Write modular and efficient ML training pipelines
Work collaboratively with researchers and application developers to customize neural network architectures. Collect performance/power data on the given hardware platform.
Develop and implement efficient algorithms for searching the space of neural network architectures for a given task and hardware configuration.
Collaborate with hardware architects to evolve future accelerators and assist in building profiling and visualization tools.
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, ****** 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.