Senior Solutions Architect, HPC

at Nvidia

📍 United States

$148,000-276,000 per year

SENIOR
✅ Remote

SCRAPED

Used Tools & Technologies

Not specified

Required Skills & Competences ?

Python @ 7 Communication @ 4 Mathematics @ 4 Parallel Programming @ 4 Debugging @ 7

Details

NVIDIA is seeking outstanding Solutions Architects to assist and support customers that are building solutions with our newest High Performance Computing (HPC) and Artificial Intelligence (AI) technologies. At NVIDIA, our solutions architects work across different teams and enjoy helping customers with the latest Accelerated Computing and Deep Learning software and hardware platforms. We're looking to grow our company, and build our teams with the smartest people in the world. Would you like to join us at the forefront of technological advancement? You will become a trusted technical advisor with our customers and work on exciting projects focused on HPC and AI. You will also collaborate with a diverse set of scientific researchers, developers and customers in Higher Education and Research. You should be comfortable working in a dynamic environment, and have experience with HPC, AI and GPU technologies. This role is an excellent opportunity to work in an interdisciplinary team with the latest technologies at NVIDIA!

Responsibilities

  • Partnering with other solution architects, engineering, product and business teams. Understanding their strategies and technical needs and helping define high-value solutions.
  • Dynamically engaging with developers, scientific researchers, data scientists.
  • Working closely with universities to help them adopt and build creative solutions using NVIDIA technology.
  • Some travel is required for this role, you are empowered to find the best way to support and make our customers successful.

Requirements

  • MS, or PhD in Computer Science, Electrical/Computer Engineering, Physics, Mathematics, other Engineering or related fields (or equivalent experience).
  • 5+ years of hands-on experience in accelerated computing and knowledge of parallel computing with GPUs.
  • Experience porting and/or optimization scientific applications targeting GPUs.
  • Strong fundamentals in programming, optimizations and software design, especially in Python and C++.
  • Strong problem-solving and debugging skills.
  • Excellent knowledge of theory and practice of Deep Learning at scale.
  • Excellent presentation, communication and collaboration skills.

Ways To Stand Out From The Crowd

  • Experience with NVIDIA GPUs and parallel programming libraries, such as CUDA, OpenMP, OpenACC, and communication runtime (MPI, NCCL, UCX, NVSHMEM).
  • Excellent C/C++ programming skills, including debugging, profiling, code optimization, performance analysis, and test design.
  • Experience working with engineering or academic research community supporting HPC or AI.
  • Familiarity with distributed computing platforms, containers and scheduling tools.