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NVIDIA

Manager, Compiler Engineering - GPU

NVIDIA is hiring a Manager, Compiler Engineering - GPU in Bengaluru, India. Level rates it ; you can apply on NVIDIA.

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • Tools and skills the posting cites include CUDA, Opencl and Opengl.
  • Level classifies it as a lead role.
  • Level lists 2,700+ other open roles at NVIDIA.

AI in this role

Software Engineering Manager leading a team to build high-performance GPU compilers for graphics and compute architectures.

cudaopenclopenglvulkancfortran
compiler-developmentgpu-architectureperformance-tuningteam-management

We are now seeking a SW Engineering Manager with strong leadership and mentoring skills to join our GPU Compilers Team. We craft outstanding compilers that realise the potential of NVIDIA's GPUs designed for solving worlds most complex problem. Our Compiler team is responsible for constructing and emitting the highest performance GPU machine instructions for Graphics (OpenGL, Vulkan, DX) and Compute (CUDA, PTX, OpenCL, Fortran, C++). This team is comprised of worldwide leading compiler engineering experts who provide leading edge performance and capabilities for NVIDIA's current and future complex parallel SIMT architectures.

In this role you will solve critical problems working alongside an outstanding engineering team with vision in Compiler technology and systems software, doing what you enjoy! Our compiler organisation makes its mark on every GPU and SoC product that NVIDIA builds. Would you like to be part of this outstanding organisation?

What you'll be doing:

  • Lead a distributed team of compiler engineers to build compiler for next generate GPU architectures.

  • Improve code generation for key applications accelerated by Nvidia GPU

  • Establish team objectives to meet schedules and goals, establish and evolve policies and procedures that affect the immediate organization, communicate with senior management for team vision and development.

  • Collaborating with members of various SW teams and the hardware architecture teams to accelerate the next generation of GPU software.

  • Insuring the scope of your team's efforts includes: helping drive performance tuning and analysis, crafting and implementing compiler and optimization techniques for workloads and other general software engineering work.

  • Mentor and coach engineers, encouraging a consistently excellent line management experience for all the engineers in the team.

  • Craft the team culture and norms in accordance with NVIDIA's values, identify gaps in being a successful team and act on them. In addition improve development practices and collaboration within the team and with others outside the team.

What we need to see:

  • Bachelors, Masters or Ph.D. or equivalent in Computer Science, Computer Engineering, related field (or equivalent experience)

  • 8+ years of production Compiler development experience with focus on compiler infrastructure, improvements to language frontends or optimizing backends.

  • 3+ years of technical lead/management experience with proven track record of delivering high quality product in timely manner.

  • Strong software design fundamentals and a deep understanding of compilers and programming languages

Ways to stand out from the crowd:

  • In depth knowledge of Processor architecture such as GPU, RISCV, ARM, x86

  • Experience with LLVM, Clang, GNU Toolchain or other compiler infrastructure.

  • Knowledge of compiler internals from front end to run-time environment

  • Experience with Embedded toolchain development

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most brilliant and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you! With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you. You will also be eligible for equity and benefits.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Manager, Compiler Engineering - GPU at NVIDIA rates 25 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Compiler DevelopmentGPU ArchitecturePerformance TuningTeam ManagementCUDAOpenclOpenglVulkan

Questions you could be asked

  1. Tell me about a project where compiler development was part of your work. What did you do?
  2. Tell me about a project where gpu architecture was part of your work. What did you do?
  3. Tell me about a project where performance tuning was part of your work. What did you do?
  4. Tell me about a project where team management was part of your work. What did you do?
  5. Walk me through how you've used CUDA in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Compiler Development, GPU Architecture, Performance Tuning, Team Management, and CUDA. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.

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