
Pioneering accelerated computing and AI
NCX Engineer, AI Accelerator at NVIDIA
About the role
NVIDIA is seeking an NCX Engineer, AI Accelerator to join our AI Accelerator team, collaborating closely with strategic customers to implement and enhance groundbreaking AI workloads! You will deliver hands-on technical assistance for advanced AI deployments, intricate distributed systems, and ensure customers realize efficient performance from NVIDIA's AI platform across varied environments. We partner with the world's most innovative AI companies to address their most challenging technical problems.
What you will be doing:
In this role, you will develop innovative solutions that advance AI infrastructure capabilities. You will directly influence customer success with breakthrough AI initiatives.
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Build and deploy custom AI solutions on NCP and Neo Cloud platforms, including distributed training, inference optimization, and MLOps pipelines constructed on NVIDIA reference architectures.
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Act as the main technical contact for strategic NCPs, offer remote and on-site support, troubleshoot complex production problems, and guide partner engineering teams on NVIDIA platform guidelines.
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Deploy and manage AI workloads across DGX Cloud, NCP data centers, and major CSP environments using Kubernetes, containers, and GPU scheduling systems aligned to NCP builds.
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Profile and tune large-scale training and inference workloads on NCP platforms. Implement observability and SLO/SLA monitoring. Lead detailed efforts to reduce latency, cost, and operational risk.
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Implement and expand NVIDIA reference architectures on partner platforms, develop integrations with partner control planes and customer environments, and ensure smooth API, data pipeline, and enterprise software connectivity.
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Build detailed implementation guides, runbooks, and post‑mortem documentation that codify standard methodologies for running NVIDIA AI workloads at scale on NCP platforms.
What we need to see:
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BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
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8+ years of experience in customer facing technical roles such as Solutions Engineering, DevOps, Site Reliability, or ML Infrastructure Engineering, ideally supporting large‑scale cloud or service provider environments.
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Strong expertise in Linux systems, distributed computing, Kubernetes, containers, and GPU scheduling on multi-tenant or service-provider platforms.
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Demonstrated AI/ML experience supporting large‑scale training and inference workloads (e.g., LLMs, generative models, recommendation systems) in production or critically important environments.
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Solid programming skills in Python/Go, with hands‑on experience using frameworks such as Py Torch or Tensor Flow for training and serving.
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Demonstrated capability to collaborate with customer and partner engineering teams in fast-paced environments, guide intricate technical investigations, and bring issues to root cause and resolution.
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Excellent communication and technical presentation skills, with the ability to clearly articulate architectures, trade‑offs, and recommendations to both engineering and leadership audiences.
Ways to stand out from the crowd:
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Experience with the NVIDIA ecosystem, including DGX systems, CUDA, Ne Mo, Triton, NIM, and NVIDIA networking technologies such as Infini Band and RoCE.
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Direct experience collaborating with NVIDIA Cloud Partners, hyperscale CSPs, or managed AI cloud platforms, including implementation of NVIDIA reference architectures for AI infrastructure.
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Deep familiarity with MLOps and cloud‑native practices: containerization, CI/CD pipelines, observability stacks (Prometheus, Grafana, Open Telemetry), and Git Ops workflows.
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Background in infrastructure as code (Terraform, Ansible, or similar) for repeatable deployment and configuration of GPU‑accelerated clusters and NCP building blocks.
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Experience integrating AI platforms with enterprise systems such as Salesforce, Service Now, or other ITSM/CRM platforms to support end‑to‑end customer solutions and managed services.
NVIDIA offers competitive salaries and a generous benefits package. It is recognized as one of the technology world’s most desirable employers. We have some of the most innovative and dedicated people working here. Due to rapid growth, our outstanding teams are expanding quickly. Join us to make a lasting impact on the world!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 9, 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.
Required skills
AI infrastructure
Distributed training
Inference optimization
Kubernetes
Containers
MLOps
Performance tuning
Customer support
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About NVIDIA

NVIDIA
PublicA computing platform company operating at the intersection of graphics, HPC, and AI.
10,001+
Employees
Santa Clara
Headquarters
$4.57T
Valuation
Reviews
10 reviews
4.4
10 reviews
Work-life balance
2.8
Compensation
4.5
Culture
4.2
Career
4.3
Management
3.8
78%
Recommend to a friend
Pros
Cutting-edge technology and innovation
Excellent compensation and benefits
Great team culture and collaboration
Cons
High pressure and expectations
Poor work-life balance and long hours
Fast-paced environment leading to burnout
Salary Ranges
79 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Analyst
7 reports
$170,275
total per year
Base
$130,981
Stock
-
Bonus
-
$155,480
$234,166
Interview experience
5 interviews
Difficulty
3.0
/ 5
Interview process
1
Application Review
2
Recruiter Screen
3
Technical Phone Screen
4
Onsite/Virtual Interviews
5
Team Matching
6
Offer
Common questions
Coding/Algorithm
System Design
Behavioral/STAR
Technical Knowledge
Past Experience
Latest updates
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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