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# Principal AI and Machine Learning Engineer

- **Company:** Hewlett-Packard Enterprise
- **Location:** Sunnyvale, CA, United States
- **Experience:** Experienced
- **Salary:** $172,000.0 - $349,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Bash Shell, Border Gateway Protocol, Network Operating System (NOS), Complex Networks, Network Congestion, Linux, Ethernet, IPv6, Junos, Python (Programming Language), Network Protocols, Open Shortest Path First (OSPF), Open Source Technology, Remote Direct Memory Access, Ansible, AI Infrastructure, Computer Network Operations, Application Specific Integrated Circuits, Git, Kubernetes, Machine Learning Operations, Docker
- **Published:** October 6, 2026
- **Apply:** https://hpe.wd5.myworkdayjobs.com/Jobsathpe/job/Sunnyvale-California-United-States-of-America/Principal-AI-and-Machine-Learning-Engineer_1216537-2

## About the Role

Bachelors + 7 years of related experience, or Masters + 4 years of related experience.
Python for automation experience.
Experience with L2/L3 network protocols such as BGP, OSPF, EVPN, VxLAN, IPv6 or similar.
Experience with Traffic tools such as Spirent, IXIA or similar.
Docker or Kubernetes experience.
Experience with network testing and validation.

Preferred Qualifications

Clear written and verbal communication skills as well as documentation skills.
SONiC, Junos, Linux or other open source network operating systems experience.
Deep understanding of Leaf-spine fabric and troubleshooting them.
Experience with Apstra and related automation tools for provisioning, managing and troubleshooting the fabric.
Experience handling complex network segmentation, security policies, and multi-site fabric designs.
Experience with RDMA, RoCEv2, PFC, ECN, congestion control, QoS, buffer behavior, and lossless Ethernet concepts.

## Description

This role has been designed as 'Hybrid' with a requirement that you will work on average 2 days per week from an HPE office., As a key contributor to AI/ML infrastructure initiatives, you will plan, execute, and analyze comprehensive benchmarks on switches, focusing on throughput, latency, congestion, incast, failover, path diversity, and workload performance to ensure optimal AI/ML network operations.

You will be guiding AI/ML workload deployments from initial scoping and test planning through execution and benchmark analysis, ensuring success criteria are met. Your role includes developing AI-driven automation workflows to streamline network development, operations, and implementations.

You will validate switch ASIC features including buffers, schedulers, QoS/queuing, ECMP behavior, telemetry, hashing, traffic distribution, and congestion visibility.

Owning switch OS configuration and automation, you will utilize SONiC, Junos, Ansible, Python, Bash, Git, and related tooling to implement and validate advanced features such as SRv6, segment routing, uSID, Adj-SID, and policy-based pathing as required. You will document PoC architecture, benchmark methodologies, topology diagrams, configurations, results, findings, and recommendations.

This role empowers you to shape the future of AI infrastructure networking by delivering scalable, high-performance, and resilient network fabrics that meet the stringent demands of AI/ML workloads, driving innovation and customer success at < >