Senior Software Engineer, Infrastructure, Google Cloud Compute

Google • Kirkland, WA

1d • $166,000 - $244,000

About The Position

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. 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’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. 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. CMCS (Cloud ML Compute Services) team is accountable for defining and driving the overall Cloud ML Compute IaaS and IaaS+ product offering and technical strategy. We are leveraging Google AI’s leadership to differentiate GCP and delight our customers with the best ML and HPC platform in the world for top talent powered by TPUs, GPUs and CPUs and all ML frameworks (e.g., TensorFlow, PyTorch and JAX). 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.

Requirements

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.

Nice To Haves

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• 1 year of experience in a technical leadership role.
• Experience designing large-scale distributed system and applying engineering best practices.
• Experience in ML model training, performance optimization and observability.

Responsibilities

• Design and implement robust telemetry systems to ingest and leverage hardware and performance data from sources, for comprehensive observability for AI/ML infrastructure.
• Develop high-impact infrastructure, tooling, and observability features that empower both internal teams and external customers to effectively monitor and troubleshoot their large-scale machine learning workloads on Google Cloud.
• Partner with ML engineers, data scientists, and ML framework teams to optimize model performance by providing essential tools and capabilities for rapid iteration and ideation.
• Lead the design and development of scalable systems with an iterative approach.
• Collaborate across organizational boundaries with cross-functional teams to align technical designs and deliver cohesive, end-to-end observability solutions for our customers.

Benefits

• 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 (statutory, where applicable); 5 days/event (discretionary)
• Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
• Baby Bonding Leave: 18 weeks
• Holidays: 13 paid days per year

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level