Senior Software Engineering Manager, ML Fleet Systems
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Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per yearNote: By applying to this position you will have an opportunity to share your preferred working location from the following: Sunnyvale, CA, USA; Kirkland, WA, USA; Seattle, WA, USA.
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience programming in C++, Java, Python, Kotlin or Go.
- 5 years of experience in a technical leadership role.
- 5 years of experience in a people management or team leadership role.
- 3 years of experience in designing, analyzing, and troubleshooting distributed systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- 5 years of experience working in a complex, matrixed organization.
- Experience with colossus and other relevant Google storage systems (e.g., Bigtable, Spanner, Woodshed).
- Experience with infrastructure optimization, performance analysis, and cost reduction in large-scale environments.
- Familiarity with Machine Learning hardware accelerators (e.g., TPUs, GPUs) and their life-cycle management.
- Understanding of resource management systems (e.g., compute infrastructure, Kubernetes, Flex), cluster management, and scheduling algorithms.
About the job
Like Google's own ambitions, the work of a Software Engineer goes beyond just Search. Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of Engineers. You not only optimize your own code but make sure Engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team. Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day. Operating with scale and speed, our exceptional software engineers are just getting started -- and as a manager, you guide the way.
With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.
Machine Learning (ML) Fleet provides demand forecasts and fulfillment options for Google's ML infrastructure, and delivers fit-for-purpose ML infrastructure on-time, cost-effectively, and at high quality. ML Fleet performs demand and capacity management for Alphabet's ML infrastructure resources across all Product Areas, ensuring those resources are allocated in line with Alphabet-wide ML priorities. ML Fleet's scope includes demand planning, capacity management, and governance of the ML fleet to execute on Google's AI-first strategy across training, serving, and enterprise offerings.
The ML Fleet Systems team’s mission is to make ML demand planning and capacity management efficient, accurate, and auditable through robust and scalable engineered solutions.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities
- Define and drive the long-term technical goal, strategy, and roadmap for critical software systems that manage Alphabet's ML fleet. This includes building systems for all ML resources such as TPUs, GPUs, compute, storage, and networking.
- Collaborate closely with engineering partners (e.g., Onefleet, Spatial Flex, ODS) to design and deliver joint engineered solutions to our customers (Product Areas within Google).
- Identify, scope, and solve broad and ambiguous challenges that impact the efficiency, reliability, and cost-effectiveness of the entire ML fleet. Turn these challenges into strategic opportunities and actionable plans.
- Drive significant improvements in ML fleet metrics, such as utilization, scheduling efficiency, and power consumption, through innovative software and system design.
- Ensure the long-term health, maintainability, and evolution of the software systems underpinning Google's AI/ML development.
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