HPE Labs - AI/ML Engineer (Technical Lead)

Hewlett Packard Enterprise • Milpitas, CA

1d • $178,000 - $361,000 • Hybrid

About The Position

Hewlett Packard Enterprise’s Office of the CTO and HPE Labs AI Enablement team turns AI research and promising ideas into dependable, governed, reusable capabilities that business units and customers can adopt. The team works between invention and practical impact, making AI production-ready and trusted at enterprise scale.

The AI/ML Engineer will serve as a technical lead, independently driving high-impact AI use cases from concept through production and operational handoff. The role sets technical direction, partners with stakeholders across functions and business units, and establishes scalable architectures, patterns, and standards that make future use cases faster and more effective. It is a hands-on senior role combining technical leadership, collaboration, stakeholder engagement, and mentoring.

The posting describes the role as primarily onsite, with an expectation of working from an HPE office, and also states “Hybrid – 2 days per week in office.” The listed U.S. base salary range for California is USD 178,000–361,000 annually; variable incentives may also be offered. Benefits information is provided through HPE’s employee benefits website, but specific benefits are not listed in the posting.

Requirements

• Typically 10 or more years of relevant experience in applied AI/ML engineering or software engineering, including hands-on delivery of AI/ML systems into production.
• Ability to take AI/ML solutions independently from concept to production, covering the full lifecycle, including data pipelines, deployment, evaluation, and operationalization.
• Experience shipping an LLM or agentic system that real users depend on, including ownership of evaluation, reliability, and operation after launch.
• Strong, current depth in AI and machine learning, including supervised and unsupervised learning, deep learning, NLP, LLMs, generative AI, agentic systems, and statistical modeling.
• Practical experience with LLMOps or MLOps, evaluation, and production model lifecycle management.
• Solid systems and software engineering fundamentals, and comfort with cloud-native and/or hybrid deployment environments.
• Working knowledge of responsible-AI and governance practices, including evaluation, guardrails, security-by-design, and data privacy.
• Bachelor’s, master’s, or PhD in computer science, computer engineering, data science, or a related field, or equivalent practical experience.
• Ability to lead technical work and influence across teams without formal authority.
• Ability to shape scalable designs, reusable patterns, and best practices with both technical depth and strategic vision.
• Excellent stakeholder and communication skills, including translating technical tradeoffs into business terms, aligning diverse groups, and building cross-functional trust.
• Track record of mentoring and developing less-experienced engineers, with an interest in helping others grow.
• Strong judgment and problem-solving skills, including determining which problems matter, when work is production-ready, and when to escalate or ask for help.

Nice To Haves

• Experience building and scaling enterprise agentic AI solutions across complex, production-grade environments.

Responsibilities

• Lead selected high-impact AI use cases from problem framing and solution design through production deployment and transition to operational ownership, using LLM, agentic, and applied AI approaches where appropriate.
• Design AI system architectures for scalability, performance, reliability, security, and supportability.
• Establish evaluation, guardrails, monitoring, documentation, and performance metrics to support trusted adoption in real workflows; improve systems using operational feedback.
• Convert delivery work into reference architectures, tooling, and repeatable patterns that reduce the cost of future use cases.
• Partner with business units, product, engineering, data, security, and HPE Labs to translate customer requirements, business needs, and industry trends into AI products, solutions, and system improvements.
• Provide technical guidance, communicate tradeoffs and impact to technical and executive stakeholders, secure sponsorship and operational ownership, and drive adoption through credibility and influence.
• Serve as a technical authority for significant AI initiatives; guide architecture and design reviews, promote engineering consistency and best practices, and mentor engineers through code reviews, design reviews, pairing, and example.
• Contribute to organizational knowledge sharing and a collaborative, high-standards team culture.
• Help shape the team’s intake, prioritization, governance, and delivery practices.

Benefits

• The company describes a comprehensive suite of benefits intended to support physical, financial, and emotional wellbeing; specific benefit offerings are not detailed in the posting.
• Career development programs intended to support employees’ professional goals.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior