Staff Software Engineer, Cloud ML Compute Services

Staff Software Engineer, Cloud ML Compute Services

As a software engineer in Cloud ML Compute Services, you will focus on delivering growth in the AI infrastructure space. The team manages the 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 top customers throughout previews, proof-of-concepts, onboarding, and production phases. You will advance AI infrastructure, support the cross-team collaboration for customer success, and are passionate about improving the performance of AI technologies. This role offers opportunities for both contributions and growth.

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.

Minimum Qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
• 8 years of experience in software development, and with full stack development, across back-end such as Python, Java, C++, or GO codebases.
• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: reinforcement learning, ML infrastructure, or specialization in another ML field.

Preferred Qualifications:

• Master's degree or PhD in Computer Science or related technical field.
• Experience with Block Storage or cloud storage systems.
• Experience with Generative AI, Large Language Models (LLM), or Machine Learning infrastructure, including model deployment, performance optimization, profiling, and debugging.
• Experience with distributed computing leveraging GPUs or TPUs.
• Ability to collaborate with cross-functional and cross-regional teams.
• Ability to grow in a fluid environment.

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 our AI/ML infrastructure delivers exceptional value and drives success for our customers.
• Identify and resolve performance bottlenecks, ensuring our infrastructure operates at the capacity.
• Support the future of our AI/ML infrastructure by identifying gaps in the existing products and recommending enhancements. Stay informed of the Artificial Intelligence and Machine Learning technologies and contribute learned expertise to foster collective team growth.