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NVIDIA

Designs the chips and software that power AI

AI Developer Technology Engineering Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • An MS or PhD in Computer Science, Computer Engineering, or in a related computationally focused science or engineering degree, or equivalent experience.
  • At least 8 years of overall relevant experience, including at least 5 years in a technical role and 3 years in an engineering leadership role.
  • In-depth expertise in linear algebra and performance optimization of Deep Learning training and inference.
  • Background in parallel programming, such as CUDA, OpenMP, MPI, and pthreads.
  • Programming fluency in C/C++ with a deep understanding of algorithms and software development.
  • Knowledge of CPU and GPU architecture fundamentals and low-level performance optimizations.
  • Excellent written and presentation skills.
  • Proven track record of planning and leading critical initiatives.

Responsibilities

  • Lead the team to optimize and develop algorithms for Machine Learning and Deep Learning applications.
  • Define and drive technical initiatives to advance the state of the art in accelerated Deep Learning and Machine Learning applications.
  • Collaborate with research, hardware, and software teams to influence the design of next-generation hardware, software, and programming models.
  • Develop and communicate technical solutions to external and internal collaborators, including technical design decisions and project plans.
  • Hire talent to join the team and promote a diverse and skilled team.
  • Coach and grow the team, promoting a culture of engineering excellence and idea proliferation.

Desired Qualifications

  • Expertise in LLMs, multimodal model architecture, and performance optimizations of relevant computational primitives.
  • Proven experience recruiting top talent.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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