채용
We are seeking a Senior Software Engineer to drive integration of the NVIDIA Grove project within Dynamo and across a set of leading open-source AI frameworks. In this role, you will develop production-grade software enabling Grove capabilities to be adopted, scaled, and operated smoothly. In this role, you will build production-grade software that enables seamless adoption, scaling, and operation of Grove capabilities across environments such as Dynamo, llm-d, Ray, Py Torch, and other emerging frameworks in the AI ecosystem. You will collaborate across engineering teams and the open-source community to deliver robust integrations, reference implementations, and developer-focused tooling.
What you'll be doing:
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Design and implement end-to-end integrations of Grove with open-source AI frameworks (e.g., Dynamo, llm-d, Ray, Py Torch, and related ecosystem projects).
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Build and maintain adapters, plugins, operators, and/or runtime components that enable Grove features to work smoothly across training and inference stacks.
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Partner with framework owners to upstream changes, contribute patches, and ensure long-term maintainability of integrations.
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Develop reference workflows, sample apps, and best-practice guides that accelerate adoption by users and partners.
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Optimize performance, scalability, and reliability for distributed training/inference, including multi-node and multi-GPU environments.
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Improve observability and operational readiness (metrics, logging, tracing, debugging tools) for Kubernetes-based deployments.
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Participate in technical design reviews, define APIs/contracts, and ensure compatibility across versions of frameworks and dependencies.
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Diagnose complex issues spanning containers, networking, scheduling, CUDA/GPU utilization, and framework runtime behavior.
What we need to see:
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BS/MS/PhD in Computer Science, Electrical Engineering, or related field (or equivalent experience)
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5+ years of proven experience in related field
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Hands-on experience integrating with at least one major AI framework/runtime (e.g., Py Torch, Ray, Triton Inference Server ecosystem, distributed runtimes, model serving stacks).
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Solid understanding of AI workloads: model development basics, training vs. inference tradeoffs, and performance considerations (throughput/latency, batching, memory).
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Experience with distributed systems concepts (RPC, scheduling, fault tolerance, resource management).
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Practical Kubernetes experience: deploying and operating services/jobs, Helm/Kustomize, operators/controllers (nice to have), and debugging clusters.
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Familiarity with containers and cloud-native tooling (Docker, container registries, CI/CD pipelines).
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Strong software engineering experience in Go, C++ and/or Python, with a track record of shipping reliable systems.
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Strong interpersonal skills and ability to collaborate across teams and with open-source communities.
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Exceptional collaboration, communication, and documentation habits.
Ways to stand out from the crowd:
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Open-source contributions to Dynamo, Py Torch, Ray, llm-d, Kubernetes ecosystem, or related ML infrastructure projects.
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Experience with large-scale model serving, distributed inference, or multi-tenant AI platforms.
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Experience building SDKs/APIs or developer tooling that improves integration usability.
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Knowledge of GPU performance profiling and optimization (Nsight tools or similar), and/or kernel-level performance tuning.
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Experience with reproducibility, packaging, versioning, and compatibility testing across fast-moving dependencies.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most experienced and hard-working people in the world working for us. Are you creative and autonomous? Do you love a challenge? If so, we want to hear from you
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 for Level 3, and 184,000 USD - 287,500 USD for Level 4.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 3, 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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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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