Google Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. 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 Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. 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 Google Kubernetes Engine (GKE) AI Platform team is responsible for managing containerized workloads and services on the AI infrastructure (GPUs/TPUs) using Kubernetes (K8s)—an open-source platform. As GKE experiences exponential growth in the AI, ML, and GenAI sectors, our team ensures that this infrastructure is automated, frictionless, and capable of managing the next generation of cloud computing.
Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge 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.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $207000 - $301000 (USD) + 20% bonus target + equity + benefits
Learn more about benefits at Google.
Responsibilities
- Act as an AI Platform TL, driving innovation on GKE AI/ML infra reliability, efficiency and scale.
- Engage with Megawhale customers to ensure their success/growth on GKE/Google Cloud Platform (GCP).
- Identify gaps and drive improvement across entire GKE/Google Compute Engine (GCE) stack.
- Help shape the culture of the team to be a high executing team that is fun to work with.
- Lead the technical goal for GKE AI/ML workload efficiency and optimization, setting the direction.
Qualifications
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development.
- 5 years of experience in cloud computing and building operating systems.
Preferred qualifications:
- Master's degree or PhD in Computer Science, Machine Learning, or a related field.
- 5 years of experience with distributed systems, data analytics, and applied ML.
- Experience with AI infrastructure (GPU/TPU, Networking, etc.) management and orchestration.
- Experience with machine learning infrastructure, large-scale distributed systems, and Cloud.
- Excellent problem-solving, code and model tuning skills.