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トレンド企業

トレンド企業

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求人NVIDIA

NIM Solutions Architect

NVIDIA

NIM Solutions Architect

NVIDIA

4 Locations

·

On-site

·

Full-time

·

1mo ago

必須スキル

Python

Docker

Git

PyTorch

NVIDIA is leading company of AI computing. At NVIDIA, our employees are passionate about AI, HPC, VISUAL, GAMING. Our Solutions Architect team is more focusing to bring NVIDIA new technology into difference industries. We help to design the architecture of AI computing platform, analysis the AI and HPC applications to deliver our value to customers. This role will be instrumental in leveraging NVIDIA's cutting-edge technologies to optimize open-source and proprietary large models, create AI workflows, and support our customers in implementing advanced AI solutions.

What you’ll be doing:

  • Drive the implementation and deployment of NVIDIA Inference Microservice (NIM) solutions

  • Use NVIDIA NIM Tools or Factory Pipeline to package optimized models (including LLM, VLM, Diffusion, Retriever, CV, OCR, AI4Science etc.) into containers providing standardized API access for on-prem or cloud deployment

  • Refine NIM tools for the community, help the community to build their performant NIMs

  • Design and implement agentic AI tailored to customer business scenarios using NIMs

  • Deliver technical projects, demos and client support tasks as directed by the Solution Architecture Leadership

  • Provide technical support and guidance to customers, facilitating the adoption and implementation of NVIDIA technologies and products

  • Collaborate with cross-functional teams to enhance and expand our AI solutions portfolio

  • Be an internal champion for NVIDIA software and total solutions in technical community

  • Be an industry thought leader on integrating NVIDIA technology especially inference services into LHA, business partners and whole community

  • Assist in supporting NVAIE team and driving NVAIE business in China

What we need to see:

  • 3+ years working experience with Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field

  • Proven experience in deploying and optimizing large language models

  • Familiarity with main stream inference engines or inference framework (e.g., SGLang, vLLM, TensorRT, or ONNX Runtime, Py Torch)

  • Strong programming skills in Python or C++

  • Experience with DevOps/MLOps such as Docker, Git, and CI/CD practices

  • Excellent problem-solving skills and ability to troubleshoot complex technical issues

  • Demonstrated ability to collaborate effectively across diverse, global teams, adapting communication styles while maintaining clear, constructive professional interactions

Ways to stand out from the crowd:

  • Experience in AI performance engineering

  • Expertise in model optimization techniques

  • Knowledge of AI workflow design and implementation; experience on cluster resource management tools

  • CUDA optimization experience, extensive experience designing and deploying large scale HPC and enterprise computing systems

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and creative people in the world working here! If you are driven by impact, passionate about enterprise AI, and inspired to shape the agentic AI at scale for NVIDIA’s Supply Chain Operations, we want to hear from you. Apply today!

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NVIDIAについて

NVIDIA

NVIDIA

Public

A computing platform company operating at the intersection of graphics, HPC, and AI.

10,001+

従業員数

Santa Clara

本社所在地

$4.57T

企業価値

レビュー

4.4

10件のレビュー

ワークライフバランス

2.8

報酬

4.5

企業文化

4.2

キャリア

4.3

経営陣

3.8

78%

友人に勧める

良い点

Cutting-edge technology and innovation

Excellent compensation and benefits

Great team culture and collaboration

改善点

High pressure and expectations

Poor work-life balance and long hours

Fast-paced environment leading to burnout

給与レンジ

79件のデータ

Junior/L3

Mid/L4

Senior/L5

Junior/L3 · Analyst

7件のレポート

$170,275

年収総額

基本給

$130,981

ストック

-

ボーナス

-

$155,480

$234,166

面接体験

5件の面接

難易度

3.0

/ 5

面接プロセス

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Onsite/Virtual Interviews

5

Team Matching

6

Offer

よくある質問

Coding/Algorithm

System Design

Behavioral/STAR

Technical Knowledge

Past Experience