Senior AI and ML Engineer - AI for Networking

About the Role

Key Responsibilities

• 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 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 such as embeddings, RAG, semantic search, and transformer-based LLMs.
• Experience with MCP workflows and Agentic ecosystem.
• Knowledge of 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 pipelines (Terraform, Ansible, Salt), monitoring (Prometheus, Grafana), and DevOps tools.
• Hands-on experience working with petabyte-scale datasets, schema design, and distributed processing.
• Ability to run simulations of network state with AI tools.

Nice to Have

• 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.
• 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 open-source automation tooling.
• Knowledge of network operating systems such as Arista EOS, Cumulus, Cisco NX-OS, Sonic, SRLinux.
• Experience with Infrastructure or Network as a Code automation frameworks.

Qualifications

• Educational background with a Bachelor's, Master's, or Ph.D. in relevant fields or equivalent experience.

Benefits & Perks

• Base salary range of $200,000 - $391,000, determined based on location, experience, and similar roles.
• Eligibility for equity and benefits.