Jobs / United States / Adobe INC

Principal Machine Learning Engineer

Adobe INC · 🇺🇸 3 Locations

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).
  • Confirmed live todayWhen 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).

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Sponsor Radar — Adobe INC

1,036 H-1B filings certified since Oct 2025

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   Firefly Foundry is Adobe's enterprise managed-service offering for custom multimedia generative AI — deep-tuned image, video, and 3D models built on each customer's IP, paired with creative production workflows and a media-intelligence layer, and deployed across new and existing Adobe surfaces and products, including Firefly, Photoshop, Illustrator, Express, Stock, and Premiere.   We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services area. This is not a model-training or research role — it is the senior-most hands-on engineering authority over how our generative models are architected,   optimized , and served at enterprise scale. You will set the inference architecture and technical standards that a growing organization of engineers builds against, co-develop and optimize the inference code that makes those systems fast and cost-efficient, and architect the APIs and product backend that let Adobe's first-party and third-party models reach both internal applications and external plugin integrations. Where the Director owns the multi-year technical strategy, headcount, and company roadmap for the org, you own the architecture, technical depth, and hands-on execution that make that strategy real — spanning multiple engineering teams without owning their people management.   What this role owns   • The technical architecture for composing,   optimizing , and serving heterogeneous generative model pipelines — LLMs, diffusion and transformer-based image/video models, RAG and retrieval systems, multi-turn agentic flows, and 3D/mesh pipelines — across the GenAI Services area.   • The optimization strategy for inference performance: latency, throughput, and cost-to-serve across model families and GPU fleets.   • The system design standards for pipeline composition, multi-tenant serving, and the product backend/API and plugin surface that integrates   first-party   and third-party generative models into Adobe's flagship products.   • Technical direction across multiple engineering teams as the principal authority on architecture and design — a cross-team scope, distinct from the Director's org-wide roadmap and   management   ownership.   Who you will partner with   • Applied Science   — to translate research models and emerging techniques into production-grade inference architecture.   • Director, ML Engineering and ML Engineering leadership   —   to align   technical architecture with organizational strategy and priorities.   • Product Managers and TPMs   — to define and deliver against the roadmap for GenAI services and APIs.   • Firefly Foundry Studio and AI Platform   — to translate creative production workflows into performant services and to   align on   shared infrastructure and serving primitives.   What you will do   • Lead the development of core GenAI services and APIs that integrate a wide range of first-party and third-party generative models into Adobe's flagship products.   • Architect ML   serving   workflows for enterprise-scale model customization, deployment, and ecosystem integration — including externalizable, self-serve fine-tuning flows.   • Co-develop and   optimize   GPU-accelerated inference pipelines — prioritizing latency, throughput, scalability, and reliability — using tools such as   PyTorch , CUDA, Triton, and   TensorRT .   • Design and   architect   the product backend and plugin ecosystem that lets internal applications and external integrations consume Firefly Foundry's model services.   • Provide hands-on technical leadership: guide engineers through architecture, design, implementation, and best practices, and mentor a growing organization of ML engineers.   • Research and evaluate emerging inference and   MLOps  

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Source: Employer career site (Workday) First seen: 2026-08-28 Last confirmed: 2026-10-02 How our data works → Report this job

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