NVIDIA redefines what’s possible. NVIDIA has been reinventing computer graphics, PC gaming, and accelerated computing for 30 years. It is a unique legacy of innovation that’s fueled by great technology and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, generative AI, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work.
Our company is at the forefront of technological innovation, and we are dedicated to driving efficiency and optimizing the performance of our infrastructure both on-prem and cloud. Join us in this exciting endeavor! We are seeking a highly skilled Principal AI/ML Engineer to join our dynamic team to build the next generation of IT Networking space and help lead the team through a major technology transformation into running AI on-prem and build infrastructure by integrating Enterprise ready platforms while building a solid foundation with automation. We are looking for a passionate engineer who will solve networking problems with AI.
What You’ll Be Doing:
Lead architecture, design, and implementation of network automation platforms across datacenter, cloud, campus, and enterprise environments.
Build source-of-truth–driven automation workflows using in-house platforms and authoritative network data models.
Design and maintain scalable data models for sites, fabrics, roles, interfaces, addressing, and deployment intent.
Generate intent-based deployment artifacts (cutsheets, cable matrices, rack elevations, port maps, deployment docs) from network models.
Build configuration generation pipelines using templating + IaC patterns to render device/service configs from model data.
Develop multi-vendor provisioning, onboarding, and ZTP workflows for network platforms and services.
Create automated validation/health-check tooling (pre/post checks, compliance, readiness) and integrate with CI/CD and ops systems.
Collaborate cross-functionally and provide technical leadership by setting standards (reliability, security, testability, docs) and mentoring engineers.
What We Need to See:
Bachelor’s degree (or equivalent experience) in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, or related field.
15+ years in network/infrastructure engineering, including 7+ years building production-grade network automation.
Strong software engineering skills in Python and Golang (required); YAML, Bash, JavaScript experience is a plus.
Proven ability to design and deliver large-scale network automation using IaC and API-driven approaches.
Hands-on experience with DCIM/IPAM / Source-of-Truth platforms (e.g., Nautobot/NetBox), including data modeling and API integration.
Experience building config generation pipelines using templating/automation frameworks (e.g., Jinja2, Ansible).
Strong experience with Terraform/Ansible (or similar), including reusable modules, versioned workflows, and pipeline integration.
Deep understanding of datacenter networking fundamentals: TCP/IP, switching/routing, BGP, EVPN/VXLAN.
Experience across multi-vendor network platforms/NOS (e.g., NVIDIA/Mellanox, Arista, Cisco, Juniper) and automating via REST/CLI with secure access patterns.
Strong DevOps mindset: CI/CD (Jenkins/GitLab), ZTP/onboarding, automated validation/compliance/health checks, strong Linux fundamentals, and clear cross-functional communication/ownership.
Ways to Stand Out From the Crowd:
Proven automation experience generating deployment artifacts from modeled intent (cutsheets, cable matrices, rack elevations, port mappings).
Experience with large-scale datacenter fabrics, including AI/ML infrastructure, GPU cluster networking, and HPC environments.
Cloud and hybrid networking expertise across Google Cloud, Azure, and Oracle Cloud, including cloud exchange/DCI providers (e.g., Equinix).
Broad multi-vendor platform experience (Arista, Cumulus, Cisco, Palo Alto, load balancers) plus observability integration (Prometheus/Grafana) tied into automation/validation workflows.
Strong platform engineering maturity: Kubernetes/containerization and Containerlab-based testing, principal-level architecture/standards/reuse, and operational documentation via Confluence/Jira/ServiceNow.
NVIDIA is 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. If you're creative and autonomous, we want to hear from you!
#LI-Hybrid
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 248,000 USD - 396,750 USD.You will also be eligible for equity and benefits.
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.Top Skills
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
