Skills this job asks for
Machine learningNegotiationLLMsLeadership
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
Employer is on a government sponsor recordThe US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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✓
What Hewlett Packard Enterprise Company paid sponsored hires in similar roles3 certified filings for “Senior AI and Machine Learning Engineer” (Data Scientists) in CA: $124k–$228k, median $174k.
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✓
Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 486 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Hewlett Packard Enterprise Company paid sponsored hires in similar roles
- 3 certified filings for “Senior AI and Machine Learning Engineer” (Data Scientists) in CA: $124k–$228k, median $174k. Most were filed at wage level I (50%) — 1 lottery entry, ≈15% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
About the role
HPE Labs - AI/ML Engineer (Technical Lead)
This role has been designed as ‘’Onsite’ with an expectation that you will primarily work from an HPE office.
Who We Are:
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.
Job Description:
Who We Are
Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. Within HPE’s Office of the CTO and HPE Labs, the AI Enablement team builds on HPE’s established AI research, engineering, and market expertise to accelerate the transition of innovation into production by turning promising ideas into dependable, governed, reusable capabilities that HPE’s business units and customers can adopt and build on.
We sit at the seam between invention and impact. We don’t just prototype; we make AI real, repeatable, and trusted at enterprise scale. The team combines HPE’s deep technical expertise with a collaborative, high-standards, and intellectually honest culture focused on solving hard problems. If you want to shape how a world-class technology company operationalizes AI, this is the team.
Role Overview
We’re hiring a technical lead for the AI Enablement team. As a tech lead, you’ll independently drive high-impact “ lighthouse ” AI use cases from concept through production: owning the technical direction, partnering across functions and business units to deliver value, and establishing scalable architectures, patterns , and standards that make each subsequent use case faster and more effective .
This is a hands-on senior role for someone who's technically excellent and genuinely good with people: equally comfortable in an architecture deep-dive, a stakeholder negotiation, and a mentoring conversation. You'll have unusual scope to shape both the work and the team from day one.
Key Responsibilities
• Lead lighthouse use cases end-to-end. Independently own selected high-impact AI use cases from problem framing and solution design through production deployment and the transition to operational ownership, bringing LLM, agentic, and applied AI approaches to bear where they fit.
• Build for production and measurable impact. Design the architecture of AI systems for scalability, performance, reliability, security, and supportability. Establish evaluation, guardrails, monitoring, documentation, and performance metrics that enable trusted adoption in real workflows, and continuously improve the systems based on operational feedback.
• Create reusable patterns. Turn each delivery into reference architectures, tooling, and repeatable patterns that lower the cost of the next use case, so the team scales through leverage, not headcount.
• Partner across the organization. Work closely 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 systems 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.
• Provide technical leadershi
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