Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- 3 years of experience with one or more of the following: speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
- 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 8 years of experience with hardware architecture and design, including Central Processing Units (CPU), Graphics Processing Units (GPU), or Tensor Processing Units (TPU).
- 5 years of experience with data structures and algorithms.
- 1 year of experience in a technical leadership role.
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.
Responsibilities
- Triage and root-cause correctness and performance issues encountered while enabling Machine Learning (ML) models on Edge Tensor Processing Unit (EdgeTPU).
- Propose and implement fixes to the compiler to address these issues in collaboration with other compiler engineers.
- Interact closely with model owners to influence their model architectures to make them run efficiently on the EdgeTPU.
- Manage project priorities, deadlines, and deliverables.
- Help build a goal and drive execution and work closely with partners and other stakeholders.