Google is looking for a Machine Learning Software Engineer to join their innovative team to research, design, and develop new technologies and hardware to make computing faster, seamless, and more powerful, aiming to make people's lives better through technology.
Requirements
- 2 years of experience with software development in one or more programming languages (C++, Python), or 1 year of experience with an advanced degree.
- 2 years of experience working with machine learning/artificial intelligence.
- Publications or research experience in deep learning.
- Experience in developing, training, and optimizing machine learning models.
- Experience working with any deep learning frameworks – Tensorflow, Pytorch or JAX.
- Experience with accelerators or working at the hardware/software interface.
- Experience with neural network architectures/design.
Responsibilities
- Lead efforts on defining, developing and training edge optimized models for generative AI, computer vision, natural language and speech use cases.
- Design, build, and maintain model optimization tools and infrastructure modules needed for automating optimization and training of neural networks and architecture design space exploration.
- Write modular and efficient ML training pipelines and assist in building profiling and visualization tools.
- Work with EdgeTPU architects to design future accelerators, the hardware/software interface, and co-optimizations of the next generation EdgeTPU architectures.
- Collaborate with ML model developers, researchers, and EdgeTPU hardware/software teams on customize neural network architectures to accelerate the transition from research ideas to user experiences running on the EdgeTPU.
Other
- Bachelor’s degree or equivalent practical experience.
- Master's degree or PhD in Computer Science or related technical field with an emphasis on Machine Learning/Artificial Intelligence.
- adaptable individual with a naturally enthusiastic and optimistic outlook who grows up in a rapidly changing environment.
- display leadership qualities and be enthusiastic to take on new problems across the full-stack
- Mountain View, CA, USA; Kirkland, WA, USA
