Google's AI and Infrastructure team is redefining what’s possible by empowering Google customers with breakthrough capabilities and insights through AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. This role will lead technical analysis across Google’s ML infrastructure to identify opportunities for efficiency gains, cost optimization, and improved resource utilization.
Requirements
- 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).
- Experience developing and driving a technical strategy and road-map that impacts multiple product areas or organizations.
- Ability to translate high-level business objectives into technical requirements and plans.
Responsibilities
- Lead technical analysis across Google’s ML infrastructure (including training, serving, and scheduling) to identify opportunities for efficiency gains, cost optimization, and improved resource utilization.
- Partner with technical leads across serving, training, scheduling, and fleet management to establish and drive technical governance, this includes defining and implementing technical policies and mandates to ensure a consistent and efficient operation of the ML fleet.
- Collaborate with Machine Learning Strategy and Allocation Committee (MLSA) leadership to translate Google's AI priorities into technical road-map for the ML compute resources, ensuring the capacity planning and allocation strategies support the most critical initiatives.
- Serve as a key technical consultant and guide for Product Areas (PAs) and engineering organizations.
- Develop and advocate technical proposals for new frameworks, tools, and systems that enable more efficient and dynamic allocation of ML resources.
Other
- Experience in a technical leadership role and leading cross-functional engineering projects from conception to completion.
- Experience presenting technical information and recommendations to executive leadership and executive stakeholders.
- Excellent problem-solving skills, with ability to use data to identify systemic issues, form hypotheses, and develop technical proposals.
- 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.
