Software Engineering Manager, Google Kubernetes AI Infrastructure
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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).
- 4 years of experience with Machine Learning Infrastructure (e.g., GPU, cloud TPU), or deep learning frameworks (e.g., TensorFlow, PyTorch, JAX), algorithms and tools (e.g., Kubeflow, Ray.io, MLflow).
- 3 years of experience in a technical leadership role; overseeing projects, with 2 years of experience in a people management, supervision/team leadership role.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience leading, designing, and implementing distributed systems.
- Experience innovating technology at scale, while motivating others to act by creating a shared sense of purpose.
- Experience building upon, contributing to open-source software projects.
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.
As an Engineering Manager on Google Kubernetes Engine (GKE) Artificial Intellignece (AI) Infrastructure, you will facilitate the strategic expansion of GKE AI Infrastructure, positioning GKE as the premier IaaS platform for deploying large-scale GenAI workloads. You will present a distinct opportunity to direct the strategy and execution of developing cloud infrastructure to support leading-edge GenAI applications, and to engage in close collaboration with our partners in serving several of Google Cloud Platforms (GCP’s) largest GenAI customers.
The US base salary range for this full-time position is $197,000-$291,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Responsibilities
- Work with multiple Google Kubernetes Engine (GKE) feature teams to build a reliable, secure, and scalable GKE service.
- Engage with customers to drive GKE Graphics Processing Unit/Tensor Processing Unit roadmap and to increase GKE/Google Cloud Platform adoption on Artificial Intelligence/Machine Learning workloads.
- Manage and coach a team of engineers to grow in their careers and overcome tests.
- Participate in Kubernetes community discussions (via SIG meetings and conferences) to guide other products and present our design and work and collaborate with other companies that are interested in this area.
- Partner with GCP teams to ship new Graphics Processing Unit/Tensor Processing Unit management features, to advance GKE’s capabilities of running massive-scale GenAI workloads.
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