Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 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.
- 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:- Master's degree or PhD in Engineering, Computer Science, or a related technical field.
- 8 years of experience with data structures and algorithms.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- Experience in ML compilers and runtimes.
- Experience with Tensor Processing Units (TPUs), TPU system design, and Graphics Processing Units (GPUs).
About the jobWe are building the ML infrastructure between top-level frameworks and hardware as a platform and operating system for ML programs. Our mission is to ensure end-to-end training and inference success for Google and the world through cost-effective and performant software stacks across hardware, frameworks, and model types.
In this role, your goal will be to enable internal and Cloud developers to innovate through the effortless, transparent use of high-functioning ML infrastructure, allowing them to focus their energy on forward-reaching achievements and the advancement of the field.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities - Innovate next directions for infrastructure over a 12-month time horizon, given a rapidly changing technology landscape.
- Drive technical strategy and roadmaps for infrastructure development.
- Identify and build stable, standardized Application Programming Interfaces (APIs) for internal products.
- Migrate existing frameworks (e.g., TensorFlow, JAX, PyTorch), runtimes (TFExecutor, TFRT, PJRT), and Product Area's custom workflows (AdBrain) onto ML Runtime, minimizing any user disruption.
- Partner with Global Delivery Model (GDM) to transfer key innovations into products developed by your team and partner teams.
