Jobs / United States / Adobe INC
Director of Engineering – Machine Learning & AI Products
Adobe INC · 🇺🇸 San Jose
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 1,036 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. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- 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. 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 Adobe INC paid sponsored hires in similar roles170 certified filings for “Machine Learning Engineer” (Data Scientists) in CA: $164k–$215k, median $184k. Most were filed at wage level II (45%) — 2 lottery entries, ≈31% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Last confirmed live 3 days agoWhen a source last listed this job as open.
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.
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Sponsor Radar — Adobe INC
The US Department of Labor certified 1,036 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. USCIS also records 221 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Adobe INC →
About the role
The Opportunity We are looking for a Director of Engineering to guide the development of AI-native, production-ready machine learning products for external clients. This leader will be responsible for the entire lifecycle of sophisticated AI systems—from product conception and rollout to production, customer engagement, and continuous operational success. This role requires a rare blend of hands‑on technical depth, product judgment, and senior‑level people leadership. You will lead a highly experienced ML engineering organization and work closely with Product, Development, and Go‑to‑Market partners to bring differentiated AI solutions to market. Key Responsibilities Technical & Product Leadership • Own the end‑to‑end delivery of AI/ML solutions deployed in production, moving beyond proofs‑of‑concept to scalable, reliable, customer‑facing systems. • Lead deep technical discussions on system build, model integration, performance, reliability, and operational readiness. • Collaborate directly with Product Management to build product vision, challenge assumptions, and ensure differentiation beyond general‑purpose LLM capabilities. • Drive architectural decisions that balance innovation, scalability, cost, and long‑term maintainability. • Act as a senior technical voice with customers, handling partner concerns, roadmap discussions, and production issue resolution. Team & Organizational Leadership • Establish, grow, and manage a high-caliber ML engineering organization, scaling the team from about 4 to over 20 engineers as time progresses. • Manage and mentor senior engineers and leaders with 16+ years of experience, encouraging accountability, ownership, and continuous growth. • Establish a flat, hands‑on, hybrid operating model where leaders stay close to the work while empowering teams to implement initiatives independently. • Conduct performance management, career development, and succession planning aligned to director‑level expectations. Execution & Operations • Ensure excellence in production operations, including monitoring, incident response, model performance, and customer‑reported issues. • Drive strong engineering rigor across testing, release readiness, and post‑launch support. • Build scalable processes that support rapid iteration while maintaining enterprise‑grade reliability. Required Qualifications • Over 15 years of experience in software engineering, with extensive expertise in machine learning or systems driven by artificial intelligence. • Demonstrated history of delivering and managing AI/ML products in production, beyond just experimentation or research. • Strong business and commercial exposure, with direct ownership or leadership of a customer-facing, revenue-impacting AI/ML product. • Strong experience with ML system build, production architecture, and real‑world operational challenges. • Demonstrated success leading senior technical teams, including performance evaluations, mentoring, and org scaling. • Ability to engage deeply with product partners and debate technical and product tradeoffs in fast paced environments. • Experience working directly with external customers and understanding customer‑facing production realities. Preferred Background • Proven track record of building AI/ML products in startup or startup-like contexts that prioritize rapid market introduction. • Background in external, customer‑facing platforms or products, particularly AI‑first offerings. • Familiarity with domains such as marketing technology, sales technology, or customer experience platforms. Leadership Attributes We Value • Hands‑on, credible technical leadership with the ability to go deep when needed. • Strong product intuition paired with engineering rigor. • Comfort operating