Tech Lead Manager, Kubernetes AI Infrastructure
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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 (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
- Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
- Baby Bonding Leave: 18 weeks
- Holidays: 13 paid days per year
Minimum qualifications:
- Bachelor’s degree, or equivalent practical experience.
- 8 years of experience with software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript).
- 3 years of experience in a technical leadership role.
- 2 years of experience in a people management or team leadership role.
Preferred qualifications:
- Master's degree or PhD in Computer Science, or a related technical field.
- 8 years of experience leading, designing and implementing large-scale distributed systems.
- 3 years of experience working in a complex, matrixed organization.
- 2 years of experience with people management.
- Experiences with deep learning frameworks (e.g., PyTorch, JAX), LLM applications and tools (e.g., SLURM, Ray).
- Experience with machine learning infra (e.g., GPU, Cloud TPU, etc.).
About the job
Like Google's own ambitions, the work of a Software Engineer (SWE) goes way beyond just Search. SWE 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 SWE Manager you manage your project goals, contribute to product strategy and help develop your team. SWE 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.
Google is looking to build the next-generation of on-prem AI infrastructure to bring the best of Google to empower Frontier model and AI solution builders to advance for AI around the world. Our team is responsible for building reliable and scalable TPU orchestration with Kubernetes. Our goal is to enable customers to effectively and reliably run their GenAI workloads by leveraging Google TPU infra at scale.
The team is on a mission to redefine the future of at-scale computing by delivering a groundbreaking, on-premises AI supercomputer experience with K8s. This is a unique opportunity to join a "special project" team creating a novel solution for customers with sophisticated security and locality requirements.
The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.
Responsibilities
- Design, guide and vet systems designs within the scope of the broader area, and write system development code to solve ambiguous problems.
- Design, develop, and maintain Kubernetes-based systems to manage large-scale TPU infrastructure for on-premises and hybrid environments.
- Oversee a team of software engineers specializing in distributed systems and AI infra, while fostering a high-performance and collaborative team environment.
- Collaborate with major frontier AI Labs to influence the AI infrastructure roadmap and promote the use of TPUs for advanced ML workloads.
- Work with cross-functional partners to deploy new infrastructure management tools that enhance Kubernetes' ability to handle large-scale GenAI tasks.
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