Senior AI and ML Engineer — AI for Networking

Details

NVIDIA is seeking a Senior AI/ML Engineer to build the next generation of IT networking capabilities by applying AI to networking problems and leading a technology transformation to run AI on-prem. The role focuses on architecting and implementing infrastructure platforms for AI/ML workloads, integrating enterprise-ready platforms, automation, and driving adoption of AIOps technologies.

Responsibilities

• Architect and implement infrastructure platforms tailored for AI/ML workloads, focusing 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/ML scientists, product managers, and domain experts.
• Build and drive adoption of emerging AIOps technologies, integrating AI Agents, RAGs, and LLMs using MCP workflows to streamline automation, performance tuning, and large-scale data insights.

Requirements

• 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: embeddings, RAG, semantic search, transformer-based LLMs.
  • MCP workflows and the agentic ecosystem.
  • Vector databases and data pipelines (examples listed: FAISS, Pinecone, Weaviate).
  • Programming in Python (preferred) and/or Go, and software engineering best practices.
• Experience deploying and tuning LLMs using techniques such as LoRA, QLoRA, and instruction tuning.
• Strong understanding of infrastructure automation pipelines (Terraform, Ansible, Salt), monitoring (Prometheus, Grafana), and DevOps tools.
• Hands-on experience working with petabyte-scale datasets, schema design, and distributed processing.
• Strong background with infrastructure-related data collections and logs related to network data, and 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 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 and demonstrated ability to communicate complex ML concepts to executive and cross-functional stakeholders.
• Strong knowledge of automation pipeline and observability tools such as BigPanda, Splunk, Storm, NetBox/Nautobot and other open-source automation tooling.
• Strong knowledge of network operating systems like Arista EOS, Cumulus, Cisco NX-OS, Sonic, SRLinux and excellence in Infrastructure/Network as Code automation frameworks.

Compensation & Benefits

• Base salary ranges by level:
  • Level 5: 200,000 USD - 322,000 USD
  • Level 6: 248,000 USD - 391,000 USD
• You will also be eligible for equity and benefits (see NVIDIA benefits).

Additional Information

• Location: Santa Clara, CA, United States
• Employment type: Full time
• Office policy: Hybrid (#LI-Hybrid)
• Applications accepted at least until July 29, 2025
• NVIDIA is an equal opportunity employer committed to diversity and inclusion.