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NVIDIA is seeking an outstanding Solutions Architect, Foundation Models to join our growing team focused on partner enablement for reasoning models, multimodal models, and production inference! In this role, you will act as both a strategic technical expert and a hands-on advisor, helping partners build, benchmark, fine-tune, optimize, and deploy foundation model solutions for customer workloads.
The Partner Solutions Architecture team acts as a trusted advisor to the ecosystem. We enable partners to translate customer requirements into architectures, benchmark recipes, cluster test plans, compute sizing, and production readiness—accelerating time to value through the full-stack accelerated computing platform.
What you'll be doing:
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Serve as the lead technical advisor for partners delivering reasoning, multimodal, fine-tuning, and model-serving solutions.
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Guide partners to the right approach for customer workloads across fine-tuning, distillation, quantization, compression, benchmarking, and evaluation.
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Define benchmark plans, synthetic data and evaluation workflows, and repeatable validation recipes.
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Advise on compute planning, including cluster sizing, GPU and network selection, storage, memory tradeoffs, latency and throughput targets, and production-readiness testing.
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Guide inference architecture across prefill and decode tradeoffs, batching, routing, disaggregated inference, and serving efficiency.
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Develop reference architectures, playbooks, benchmark recipes, TCO calculators, and sizing models across CUDA, Ne Mo, Nemotron, Dynamo, TensorRT-LLM, Triton, NIMs, and related tooling.
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Support pre- and post-sales engagements by translating complex model and infrastructure topics for partner and customer teams.
What we need to see:
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MSc, PhD in Computer Science, Electrical Engineering, Software Engineer, ML Engineer, or related fields (or equivalent experience).
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5+ years of relevant experience working with LLMs, VLMs, and large-scale inference systems, with hands-on expertise in fine-tuning, benchmarking, evaluation, optimization, and production deployment as a Research Engineer, Deep Learning Engineer, or equivalent.
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Strong understanding of foundation models across data preparation, fine-tuning, post-training, evaluation, and inference.
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Familiarity with reasoning models, reinforcement learning, and synthetic data generation and evaluation workflows.
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Strong programming skills in Python and hands-on experience with Py Torch, JAX, or Tensor Flow.
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Familiarity with Nemotron, Ne Mo, Dynamo, TensorRT-LLM, Triton, vLLM, and similar inference and optimization stacks.
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Strong communication and presentation skills, with the ability to advise both technical teams and executives.
Ways to stand out from the crowd:
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Experience helping partners or customers deploy large-scale AI systems in production.
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Built benchmark suites, fine-tuning recipes, sizing calculators, or TCO models for AI workloads.
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Strong knowledge of GPU infrastructure, including NVLink, Infini Band, MPI, NCCL, or adjacent cluster technologies.
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Active OSS contributions in model tooling, inference, evaluation, or performance optimization.
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Comfortable moving between deep technical reviews, architecture guidance, benchmarking, and partner enablement.
Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 11, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
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.
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NVIDIA 소개

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
직원 수
Santa Clara
본사 위치
$4.57T
기업 가치
리뷰
4.1
10개 리뷰
워라밸
3.5
보상
4.2
문화
4.3
커리어
4.5
경영진
4.0
75%
친구에게 추천
장점
Great culture and supportive environment
Smart colleagues and excellent people
Cutting-edge technology and learning opportunities
단점
Team-dependent experience and outcomes
Work-life balance issues with long hours
Politics and influence over competence
연봉 정보
73개 데이터
Junior/L3
Mid/L4
Junior/L3 · Analyst
7개 리포트
$170,275
총 연봉
기본급
$130,981
주식
-
보너스
-
$155,480
$234,166
면접 경험
7개 면접
난이도
3.1
/ 5
경험
긍정 0%
보통 86%
부정 14%
면접 과정
1
Application Review
2
Recruiter Screen
3
Online Assessment
4
Technical Interview
5
System Design Interview
6
Team Review
자주 나오는 질문
Coding/Algorithm
System Design
Technical Knowledge
Behavioral/STAR
뉴스 & 버즈
Negotiating NVIDIA's Offer
Base, stock, and sign-on negotiable. Recruiters invested in closing candidates. CEO reviews all 42K employee salaries monthly. Stock growth has made many employees millionaires.
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NVIDIA Company Reviews
WLB rated 3.9/5 (lowest category). 64% satisfied with WLB but 53% feel burnt out. Compensation rated 4.4-4.5/5. Experience highly team-dependent.
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NVIDIA Interview Discussions
Technical bar is high with 4-6 rounds. Process takes 4-8 weeks. Expect C++ questions, LeetCode medium, and system design. Difficulty rated 3.16/5.
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NVIDIA Culture Discussions
Team-dependent experience; sink-or-swim culture that rewards high performers but can be overwhelming. No politics, flat structure, but demanding workload with some teams requiring evening/weekend work.
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