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Deep Learning Solution Architect - EBC

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NVIDIA

9d ago

  • Job
    Full-time
    Junior Level
  • Data
    Software Engineering
  • Quick Apply

AI generated summary

  • You need a B.Tech in a relevant field, 2+ years in Deep Learning, expertise in LLMs, experience with supercomputing, and strong communication, teamwork, and problem-solving skills.
  • You will guide customers through the sales process for GPU products, manage technical relations, organize workshops, and promote Deep Learning within the NVIDIA technical community.

Requirements

  • What we need to see:
  • B.Tech. in Engineering, Mathematics, Physics, or Computer Science, MS desirable. as well as 2+ years of Deep Learning experience
  • Experience working with modern Deep Learning software architecture and application
  • Customer facing skill-set and background as well as the ability to communicate effectively with customers
  • Exposure to BCM, Infrastructure management, SLURM, K8, storage, InfiniBand is must
  • Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, Pytorch, or Hugging Face Transformers.
  • Experience working with supercomputing and technical computing customers
  • Strong teamwork and interpersonal skills; able to multitask in a fast paced environment
  • Strong analytical and problem-solving skills
  • Ability to balance multiple accounts during implementation of new technology and products into very complex projects

Responsibilities

  • Assist field business development in guiding the customer through the sales process for GPU Computing products, owning the technical relationship, and assisting customer in building innovative solutions based on NVIDIA technology.
  • Be responsible for LAB and EBC. All customer visits and engagements along with organizing workshops and hands on trainings.
  • Be an internal champion for Deep Learning or Data Science among the NVIDIA technical community.

FAQs

What is the primary role of a Deep Learning Solution Architect at NVIDIA?

The primary role involves guiding customers through the sales process for GPU Computing products, managing technical relationships, and assisting them in building innovative solutions based on NVIDIA technology.

What qualifications are required for this position?

A B.Tech. in Engineering, Mathematics, Physics, or Computer Science is required, with an MS being desirable, along with 2+ years of Deep Learning experience.

What types of customers will I be working with?

You will be working with supercomputing and technical computing customers, including those interested in LLM, MLLM, Generative AI, and RAGs.

Are there any specific technical skills or experiences required for this role?

Yes, experience with deep learning software architecture, training and fine-tuning LLMs using frameworks like TensorFlow, PyTorch, or Hugging Face, and knowledge of BCM, infrastructure management, SLURM, K8, storage, and InfiniBand are required.

Is customer-facing experience important for this role?

Yes, a customer-facing skill-set and the ability to communicate effectively with customers are essential for this position.

What tools and technologies will I need to be familiar with?

Familiarity with GPU technologies, GPU cluster management, large scale and cluster computing, and distributed computing concepts is important for this role.

Will I need to travel for this position?

Yes, occasional travel is required for local on-site visits to customers and data science conferences.

What are the key responsibilities associated with LAB and EBC?

You will be responsible for all customer visits and engagements, as well as organizing workshops and hands-on training sessions.

What qualities or skills would help a candidate stand out for this role?

Specialty skills in large scale computing, parallel computing expertise, and hands-on experience with designing efficient workflows for LLM training and inference on GPU clusters would help a candidate stand out.

Does NVIDIA promote diversity and inclusion within its workforce?

Yes, NVIDIA is committed to fostering a diverse work environment and is proud to be an equal-opportunity employer, ensuring no discrimination based on various protected characteristics.

Manufacturing & Electronics
Industry
10,001+
Employees
1993
Founded Year

Mission & Purpose

Since its founding in 1993, NVIDIA (NASDAQ: NVDA) has been a pioneer in accelerated computing. The company’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined computer graphics, ignited the era of modern AI and is fueling the creation of the metaverse. NVIDIA is now a full-stack computing company with data-center-scale offerings that are reshaping industry.