Staff Software Engineer, GenAI, Performance Engineering

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:

• Experience in a technical leadership role and leading cross-functional engineering projects from conception to completion.
• Experience developing and driving a technical strategy and road-map that impacts multiple product areas or organizations.
• Experience presenting technical information and recommendations to executive leadership and executive stakeholders.
• Ability to translate high-level business objectives into technical requirements and plans.
• Excellent problem-solving skills, with ability to use data to identify systemic issues, form hypotheses, and develop technical proposals.

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.

The ML, Systems, & Cloud AI (MSCA) organization at Google designs, implements, and manages the hardware, software, machine learning, and systems infrastructure for all Google services (Search, YouTube, etc.) and Google Cloud. Our end users are Googlers, Cloud customers and the billions of people who use Google services around the world.

We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Google Cloud’s Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.

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.