Principal AI and ML Engineer — AI for Networking - job 2 of 2

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:

• Architect and implement infrastructure platforms tailored for AI/ML workloads, with a focus on scaling private cloud environments to support high-throughput training, inference, and Agentic workflows and pipelines.

• Lead initiatives in Generative AI systems design, including Retrieval-Augmented Generation (RAG), LLM fine-tuning, semantic search, and multi-modal data processing.

• Build and optimize ML systems for document understanding, vector-based retrieval, and knowledge graph integration using advanced NLP and information retrieval techniques.

• Design and develop scalable services and tools to support GPU-accelerated AI pipelines, leveraging Kubernetes, Python/Go, and observability frameworks.

• Mentor and collaborate with a multidisciplinary team of network engineers, automation engineers, AI and ML scientists, product managers, and multiple domain experts.

• Build and drive adoption of emerging AIOPs technologies, integrating AI Agents, RAGs, and LLMs using MPC workflows to streamline automation, performance tuning, and large-scale data insights.

What We Need to See:

• 10+ years of engineering experience with at least 5 years leading initiatives in ML infrastructure, AI systems, or applied NLP/LLM development.

• 5+ years of experience in Networking and infrastructure.

• Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Machine Learning, or a related field (or equivalent experience).

• Deep expertise with:

  • Generative AI concepts such as embeddings, RAG, semantic search, and transformer-based LLMs

  • MPC workflows and Agentic ecosystem

  • Vector databases (e.g., FAISS, Pinecone, Weaviate) and data pipelines

  • Programming in Python (preferred) and/or Go, and software engineering best practices

• Experience deploying and tuning LLMs using techniques like LoRA, QLoRA, and instruction tuning.

• Strong understanding of infrastructure automation pipeline (Terraform, Ansible, Salt), monitoring (Prometheus, Grafana), and DevOps tools.

• Hands-on experience working with petabyte-scale datasets, schema design, and distributed processing.

• Strong background in working with infrastructure related data collections and logs related to network data. Ability to run simulations of network state with AI tools.

Ways to Stand Out From the Crowd:

• Experience building multi-hop RAG systems with self-consistency and chain-of-thought prompting.

• Prior leadership in designing AI platforms used for large-scale enterprise search, document intelligence, or recommendation systems.

• Contributions to open-source ML/AI tools or active participation in the AI research community.

• Familiarity with knowledge graph construction and reasoning systems as well as demonstrated ability to communicate complex ML concepts to executive and cross-functional stakeholders.

• Strong knowledge of automation pipeline and infrastructure configuration and observability tools like: BigPanda, Splunk, Storm, Netbox/Nautobot and different open-source automation tooling

• Strong knowledge of different "network operating systems" like Arista EOS, Cumulus, Cisco NX-OS, Sonic, SRLinux as well as excellence in Infrastructure or Network as a Code automation frameworks

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-Hyrbrid

The base salary range is 248,000 USD - 391,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.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.