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Sunnyvale

    Engineering Manager, High Performance Computing Machine Learning Networking - Sunnyvale, TX, United States - Google

    Google
    Google Sunnyvale, TX, United States

    3 weeks ago

    Default job background
    Description

    Minimum qualifications:

    Bachelor's degree or equivalent practical experience.8 years of experience with software development in one or more programming languages (e.g., C, C++, etc.).3 years of experience in a technical leadership role; overseeing projects, with 5 years of experience in a people management, supervision/team leadership role.

    Experience with Networking Protocols, Linux, Machine Learning Infrastructure, and High Performance Computing (HPC).


    Preferred qualifications:


    Master's degree or PhD in Engineering, Computer Science, or a related technical field.5 years of experience working in a complex, matrixed organization.

    Experience with NCCL, MPI, Libfabric, RDMA, TCP/IP, Performance. About the job Like Google's own ambitions, the work of a Software Engineer goes way beyond just Search.

    Software Engineering Managers have not only the technical expertise to take on and provide technical leadership to major projects, but also manage a team of engineers.

    You not only optimize your own code but make sure engineers are able to optimize theirs. As a Software Engineering Manager you manage your project goals, contribute to product strategy and help develop your team.

    Teams work all across the company, in areas such as information retrieval, artificial intelligence, natural language processing, distributed computing, large-scale system design, networking, security, data compression, user interface design; the list goes on and is growing every day.

    Operating with scale and speed, our exceptional software engineers are just getting started and as a manager, you guide the way.

    With technical and leadership expertise, you manage engineers across multiple teams and locations, a large product budget and oversee the deployment of large-scale projects across multiple sites internationally.

    Google Cloud High Performance Computing (HPC) Machine Learning (ML) Networking is responsible for innovations and optimizations of the networking stack to make Machine Learning High Performance Computing (HPC) workload performant on Google Cloud Platform (GCP) and in Google production.

    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 Lead the team in boosting networking performance for Machine Learning and HPC applications in Google Cloud and production.

    Work across teams/organizations to identify new opportunities for the team to utilize their expertise to help increase applications' throughput and efficiency.

    Develop team members, and foster an inclusive and impact driven culture.
    Enhance or build internal and external partnerships with core Machine Learning, Deepmind, GPU vendors, etc.

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