Software Engineer III, ML Networking
at Alphabet
Posted 3 hours ago
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- Compensation
- $141,000 – $202,000 USD
- City
- Not specified
- Country
- United States
Currency: $ (USD)
Google is seeking a Software Engineer III to work on ML networking infrastructure and performance. In this role you will learn about large language models and ML workloads, and help build infrastructure to scale ML to GPUs and trillions of parameters. You will analyze networking issues in next-generation GPU hardware, optimize workloads, and execute full-stack optimizations across the Google infrastructure. The position emphasizes collaboration across teams to push ML networking performance and scalable systems.
Software Engineer III, ML Networking
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Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development or 1 year of experience with an advanced degree in an industry setting.
- 2 years of experience with developing large-scale infrastructure, distributed systems or networks, or experience with compute technologies, storage or hardware architecture.
- Experience in networking.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with data structures and algorithms.
- Experience developing accessible technologies.
About the job
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.In this role, you will learn about the Large Language Models (LLM's) and other Machine Learning (ML) workloads, and how to build the infrastructure to scale them to Graphics Processing Unit (GPUs) and trillions of parameters.
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.The US base salary range for this full-time position is $141,000-$202,000 + 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.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Analyze the networking issues associated with the next generations of GPU hardware, and design, build, and deploy whatever is needed to make them work optimally in our data centers.
- Achieve workload optimal performance NVIDIA Collective Communications Library (NCCL) + Graphics Processing Unit (GPU).
- Compile a comprehensive analysis of performance across different GPU and network generations.
- Determine how customers' ML models will evolve once we have 72 node-NVLink domains.
- Execute full stack optimization for ML networking performance on Google's infrastructure, this spans a wide range, from kernel optimization, user space communication libraries.
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Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
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