HPE Labs - AI/ML Engineer (Technical Lead)

Hewlett Packard Enterprise • Milpitas, CA

1d • $178,000 - $361,000 • Onsite

About The Position

Hewlett Packard Enterprise’s Office of the CTO and HPE Labs AI Enablement team helps transition AI innovation into production by turning promising ideas into dependable, governed, reusable capabilities. The team works between research and real-world application, helping HPE business units and customers adopt AI at enterprise scale.

The Technical Lead independently drives high-impact AI use cases from concept through production and operational ownership. This hands-on senior role sets technical direction, partners across functions and business units, and establishes scalable architectures, patterns, and standards. It combines technical leadership with stakeholder collaboration, mentoring, and opportunities to shape the team’s practices and direction.

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 that real users depend on, with responsibility for 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, 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.
• Strong technical depth and strategic vision to shape scalable designs, reusable patterns, and best practices.
• Excellent stakeholder and communication skills, including translating technical tradeoffs into business terms, aligning diverse groups, and building trust across functions and business units.
• Track record of mentoring and developing less-experienced engineers, with an interest in helping others grow.
• 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 across 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.
• Design AI system architectures for scalability, performance, reliability, security, and supportability.
• Establish evaluation, guardrails, monitoring, documentation, and performance metrics for trusted adoption in real workflows, and improve systems based on operational feedback.
• Create reference architectures, tooling, and repeatable patterns that reduce the cost and effort of future use cases.
• Partner with stakeholders across business units, product, engineering, data, security, and HPE Labs to translate requirements, business needs, and industry trends into AI products, solutions, and system improvements.
• Provide technical guidance, explain tradeoffs and impact to technical and executive stakeholders, secure sponsorship and operational ownership, and drive adoption through credibility and influence.
• Guide architecture and design reviews, promote engineering best practices, and mentor less-experienced engineers through code reviews, design reviews, pairing, and example.
• Contribute to organizational knowledge sharing and cultivate 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.
• Personal and professional development programs to support career goals.

What This Job Offers

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