Jobs / United States / Adobe INC
Staff Machine Learning Engineer
Adobe INC · 🇺🇸 2 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).
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 Join Adobe’s Brand AI Services team and help define the future of AI-powered creativity . We are building multimodal and agentic AI systems that enable marketers and creative professionals to ideate, create, understand, and transform content through intelligent AI-powered workflows. As a Staff Machine Learning Engineer , you will design and deliver production-grade generative and agentic AI systems that power Adobe Firefly AI Assistant and experiences across Creative Cloud, Adobe Express, GenStudio, and more. You’ll work at the intersection of computer vision, generative AI, multimodal learning, and agentic AI , building systems that understand creative intent, reason across multimodal content, use tools, and orchestrate complex creative workflows. This is a high-impact role focused on building the next generation of AI experiences for millions of creative professionals. Come create the future with us! What You’ll Do • Lead the design, development, and deployment of multimodal and generative AI systems spanning vision, language, and other modalities. • Build and productionize generative AI models and systems , including transformers, diffusion models, LLMs, and vision-language models (VLMs), for content creation, understanding, and transformation. • Develop and build agentic AI systems that can reason, use tools, interact with models and services, and complete complex multi-step creative workflows. • Build intelligent capabilities for Firefly AI Assistant and Creative Cloud workflows , helping creative professionals move from intent and ideas to high-quality creative outcomes. • Develop scalable services and APIs that integrate AI and machine learning capabilities into Adobe products. • Drive the end-to-end ML lifecycle, including problem formulation, modeling, experimentation, evaluation, deployment, monitoring, and iteration. • Partner with engineering, product, design, and research teams to translate customer needs into effective ML solutions. • Improve the performance, scalability, reliability, and quality of AI systems operating in high-traffic production environments. • Provide technical leadership, mentor engineers, and help raise the engineering and machine learning bar across the team. • Identify new opportunities to apply generative and agentic AI to real-world challenges for creative professionals and enterprise customers. What You Need to Succeed • MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience. • 5+ years of experience building and deploying machine learning systems in production. • Hands-on experience designing and building agentic AI systems , including areas such as tool use, agent orchestration, multi-step workflows, planning and reasoning, retrieval, memory, or human-in-the-loop systems . • Experience with agent interoperability and tool integration , including Model Context Protocol (MCP) , function/tool calling, or similar frameworks and protocols. • Expertise in computer vision, generative AI, and/or multimodal machine learning , with hands-on experience using modern architectures such as transformers, diffusion models, LLMs, or VLMs. • Solid foundation in probability, statistics, machine learning, and model evaluation . • Proficiency in Python and experience with machine learning frameworks such as PyTorch . • Experience designing and building scalable APIs, distributed services, or production ML infrastructure . • Strong software engineering fundamentals, including data structures, algorithms, testing, code quality, and code reviews. • Experience with cloud platforms such as AWS or Azure and containerization and orchestration technologies such as Docker and Kubernetes. • Familiarity with modern AI-assisted develop