Senior Software Engineer, Cloud ML Compute Service
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Minimum qualifications:
- Bachelor’s degree in Computer Science or equivalent practical experience.
- 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
- 3 years of experience with full stack development, across back-end such as Python, Java, C++, or GO codebases.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
Preferred qualifications:
- Master's degree or PhD in Computer Science or related technical field.
- Experience with Generative AI, Large Language Models (LLM), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging.
- Experience with cloud services in the areas of Compute, Virtual Machines, Storage, or Networking.
- Experience with distributed computing leveraging GPUs or TPUs.
- Ability to grow in a fluid environment where the AI technologies are advancing.
- Ability to collaborate with cross-functional and cross-regional teams.
About the job
As a software engineer in Cloud ML Compute Services, you will focus on delivering growth in the AI infrastructure space. The team manages challenges by optimizing ML workload performance at every layer across the technical stack from networking and data storage to ML models, designing custom ML solutions from prototype to production, and providing technical guidance to customers throughout previews, proof-of-concepts, on-boarding, and production phases. You will manage challenges, and take accountability for the success of the users and customers as we drive technology forward.
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.Responsibilities
- Measure and enhance performance on Google Cloud across the technical stack, including storage, networking, and model throughput.
- Conduct performance profiling, debugging, and troubleshooting of AI/ML training and inference workloads.
- Partner with cross-functional, cross-regional teams to ensure the AI/ML infrastructure delivers excellent value and drives success for the customers.
- Identify and resolve performance bottlenecks, ensuring the infrastructure operates at optimal levels.
- Support the future of the AI/ML infrastructure by identifying gaps in the existing products and recommending enhancements.
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