HPE Labs - AI/ML Engineer (Technical Lead)

Hewlett Packard Enterprise • Milpitas, CA

7d • $178,000 - $361,000 • Onsite

About The Position

Hewlett Packard Enterprise’s Office of the CTO and HPE Labs AI Enablement team works to move AI innovation into production by creating dependable, governed, reusable capabilities for HPE business units and customers. The team bridges research and practical enterprise impact, making AI repeatable and trusted at scale.

The AI/ML Engineer is a hands-on technical lead who independently drives high-impact AI use cases from initial problem framing and solution design through production deployment and transition to operational ownership. The role sets technical direction, partners across functions and business units, and establishes scalable architectures, patterns, and standards. It combines deep technical work with stakeholder engagement, technical leadership, and mentoring, while helping shape the team’s practices and culture.

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 independently take an AI/ML solution from concept to production across the full lifecycle, including data pipelines, deployment, evaluation, and operationalization.
• Experience shipping an LLM or agentic system used by real users, with ownership of its evaluation, reliability, and operation after launch.
• Strong current knowledge of AI and machine learning, including supervised and unsupervised learning, deep learning, natural language processing, large language models, 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 or master’s degree 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 through technical depth and strategic vision.
• Strong stakeholder and communication skills, including the ability to explain technical tradeoffs in business terms, align diverse groups, and build trust across functions and business units.
• Track record of mentoring and developing less-experienced engineers, with an interest in growing others.
• Strong judgment and problem-solving skills, including assessing 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 in complex, production-grade environments.

Responsibilities

• Own selected high-impact AI use cases end-to-end, from problem framing and solution design through production deployment and transition to operational ownership; apply LLM, agentic, and other 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, and improve systems based on operational feedback.
• Turn delivered work into reference architectures, tooling, and repeatable patterns that reduce the cost and effort of subsequent use cases.
• Partner with stakeholders across 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.
• Lead architecture and design reviews, promote consistency and engineering best practices, and mentor less-experienced engineers through code reviews, design reviews, pairing, and example.
• Contribute to organizational knowledge sharing and foster a collaborative, high-standards team culture.
• Help develop the team’s intake, prioritization, governance, and delivery practices.

Benefits

• Comprehensive benefits intended to support physical, financial, and emotional wellbeing.
• Career-development programs to help employees pursue career goals, become subject-matter experts, or apply their skills in another division.

What This Job Offers

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