Staff Software Engineer, Machine Learning Infrastructure, Google Cloud
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Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 8 years of experience in software development, and 3 years of experience in SLURM.
- 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
- 5 years of experience with one or more general purpose programming languages (e.g., C++ or Python).
- 5 years of experience with AI Infrastructure and HPC.
Preferred qualifications:
- Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
- 3 years of experience in a technical leadership role leading project teams and setting technical direction.
- 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
- 3 years of experience working with distributed computing.
- 3 years of experience with product development.
- Experience with open source contributor.
About the job
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.
AI and high-performance computing (HPC) are the fastest-growing areas in tech, and Google is committed to leading the way. Our Cloud Machine Learning (ML) Compute Services (CMCS) team builds tools and infrastructure to make the most of AI hardware. You will focus on making sure AI and HPC run smoothly and efficiently on Google's Cloud platform.
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 $189,000-$284,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. 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
- Help to build and ship solutions in Google Cloud Platform.
- Define and execute the technical strategy for new products supplying compute resources to large AI/ML and HPC customers.
- Design and develop systems by defining incremental milestones, enabling rapid iteration for new use cases.
- Help hire and grow team members who are passionate about building large scale systems, tooling, and solutions.
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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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