Jobs at Nvidia

At NVIDIA, we're solving the world's most challenging problems with our unique approach to accelerated computing. We're looking for passionate technologists with software and semiconductor manufacturing background and EDA domain expertise to engage startup developers in the semiconductor manufacturing community. In this developer enablement role, you will drive NVIDIA platform adoption with EDA startups. You'll define and deliver strategic partnerships, lead fruitful technical collaborations, provide first-line technical expertise, and guide NVIDIA's product strategy as a representative of developers in the semiconductor/EDA ecosystem. The Industrial Engineering organization is a strong, growing, and visible group both inside and outside of NVIDIA in this exciting area to drive strategy. We are looking for a self-starting leader to continue to grow this area. Do you thrive on technical engagement? Do you have the rare blend of both technical and relationship skills? Are you passionate about groundbreaking technology? If so, we would love to learn more about you! What you'll be doing: • Create fruitful technical engagements across the semiconductor design and manufacturing startup ecosystem and lead strategic relationships with key opinion leaders, top developers and ISVs, and influential researchers. • Inform NVIDIA's strategy for semiconductor manufacturers and EDA/CAE ISVs by working with diverse teams including Product, Engineering, Marketing, Applied Research, etc. • Use your technical expertise to discover high impact problems NVIDIA can uniquely solve that create new market paradigms. • Drive early adoption of new products and support launch and go-to-market activities. • Activate relationships with higher education and research and speak at relevant scientific, technical and industry conferences. What We Need To See: • 12+ years of experience with EDA ISVs or semiconductor designers/manufacturers, e.g. Cadence, Synopsys, Siemens, ASML, AMAT, KLA, Lam Research, Samsung, SK Hynix, TSMC, Intel, etc. • A track record of defining and delivering impactful technical engagements, managing technical and business alliances across multiple partner groups, and working with peer teams to achieve objectives. • World-class communication skills with a demonstrated ability to articulate a value proposition to technical and non-technical audiences. • MS/PhD in Computer Science or Engineering or equivalent experience. Ways To Stand Out From The Crowd: • Developer experience creating tools and/or solutions for EDA, high-performance computing, applied machine learning, or deep learning. • Experience with AI physics models and model architecture including developing, defining, training, and deploying open or proprietary models. • Experience with NVIDIA products and SDKs: CUDA, CUDA-X Libraries, PhysicsNeMo, Omniverse, etc. With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous person with a real passion for technology, 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 224,000 USD - 356,500 USD. You will also be eligible for equity and benefits. Applications for this job will be accepted at least until February 2, 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.

NVIDIA has been at the forefront of innovation for two decades. • Reinventing itself through its invention of GPU in 1999 Key execution initiatives involve introducing next-generation AI supercomputers working alongside HPC engineers and technologists.

NVIDIA has been at the forefront of innovation for two decades. • Reinventing itself through its invention of GPU in 1999 Key execution initiatives involve introducing next-generation AI supercomputers working alongside HPC engineers and technologists.

Job Description

In this role, you’ll make an impact in the following ways:

 

• Be hands-on with enterprise-grade NVIDIA AI infrastructure, supporting GPU-based compute, high-performance storage, and network systems designed for ML/AI at scale.

 

• Deploy, monitor, and troubleshoot containerized AI workloads using Kubernetes, Docker, and GPU orchestration tools like Run:AI and NVIDIA BCM.

 

• Own the observability of our AI platforms—monitor health, identify performance bottlenecks, and make strategic recommendations to drive platform reliability and maturity.

 

• Automate infrastructure operations and provisioning using Python, Bash, and tools like Terraform or Ansible to reduce manual toil and accelerate experimentation.
• Maintain and scale AI training and inference pipelines, integrating infrastructure workflows into CI/CD systems to enable seamless, automated deployment of AI workloads.

To be successful in this role, we’re seeking the following:

• Bachelor's degree in computer science or a related discipline, or equivalent work experience required; advanced degree preferred8-10 years of related experience required; experience in the securities or financial services industry is a plus.
• Experience with Linux administration (RHEL/Ubuntu), shell scripting, and system-level debugging.

 

• Proven experience running distributed systems in Kubernetes and containerized environments -using Docker.

 

• Familiarity with GPU resource management, including NVIDIA GPU Operator and device plugin lifecycle.

 

• Experience with CI/CD workflows and infrastructure automation tools such as GitLab CI, Jenkins, Terraform, Helm, or Ansible.

 

• Knowledge of networking fundamentals and persistent storage systems.

 

• Exposure to cloud platforms (AWS, GCP, Azure) and hybrid GPU environments.

 

• Ability to read and support Python code focused on ML/AI pipeline integration.

 

• Strong analytical and troubleshooting skills with a collaborative mindset.

 

Effective communication skills and proactive ownership of platform reliability and performance.

Regards,

Mohammed ilyas,

PH - (phone number removed) or Text - (phone number removed) or you can share the updated resume at Mohammed@vtekis. com

Title: Machine Learning/AI Engineer with Python – NVIDIA GPU
Location: SAN JOSE, CA
Duration: 6 months
Machine Learning 7+ years

Job Description:  Candidates should have experience with NVIDIA GPUs for machine learning, proficiency in GPU frameworks (CUDA, cuDNN, TensorRT, NCCL),and  strong programming skills in Python with major frameworks like PyTorch and TensorFlow. Understanding of GPU architecture and performance optimization, experience with profiling tools, and  knowledge of distributed training and containerization are also required.