Jobs / United States / Adobe INC
Staff Applied Scientist - 3D Synthetic Data
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 roles18 certified filings for “Applied Scientist” (Information Technology Project Managers) in CA: $174k–$215k, median $212k. Most were filed at wage level III (46%) — 3 lottery entries, ≈46% 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
Adobe's Applied Science & Machine Learning (ASML) organization is looking for applied research scientists to help us build the next generation of multimodal foundation models. We are seeking candidates with strong technical expertise in 3D/4D content generation, simulation and game engine workflows, agentic systems, and scalable data pipelines. We are particularly interested in candidates who enjoy working across traditional research and engineering boundaries and are excited about building novel systems for future foundation model training. As a n applied research scientist at ASML, you will join a world-class team of applied researchers and engineers developing the future of creative intelligence. You will have the opportunity to work on large-scale 3D/4D data generation, simulation-driven content creation, and agentic workflows that will power next-generation multimodal AI systems. What you will be responsible for : • Develop large-scale pipelines for generating, curating, and validating 3D and 4D assets for foundation model training. • Develop simulation-based data generation systems using game engines and digital environments. • Build agentic workflows that use AI systems to create, manipulate, repair, annotate, evaluate, and refine 3D and 4D content. • Design and implement asset integration pipelines for meshes, materials, textures, rigs, skeletal animation, blendshapes , motion clips, scene graphs, lighting, cameras, and physics metadata. • Design tools and infrastructure for procedural asset creation, animation generation, motion synthesis, and interactive content generation. • Advocate and set patterns for software development to scale up synthetic data generation. • Collaborate with researchers and engineers across foundation models, multimodal learning, graphics, and data systems. What you'll need to succeed: • BS, MS, or PhD in Computer Science, AI/ML, Computer Graphics, Robotics, Game Development, or related fields. • Strong programming skills in Python and C++, with experience building reliable production quality software. • Experience with game engines or 3D engines such as Unreal Engine, Unity, Blender, CARLA, Isaac Sim, Omniverse, or similar systems. • Experience building scalable 3D data pipelines, including ingestion, transformation, validation, export, and quality control for assets, scenes, animation, and generated content. • Strong working knowledge of 3D content systems, including meshes, materials, textures, scene structure, cameras, lighting, coordinate systems, skeletal animation, and motion workflows. • Experience with procedural generation for assets, scenes, environments, characters, or simulation scenarios. • Strong problem-solving skills and the ability to learn new technologies quickly. • Excellent communication skills and the ability to collaborate across research and engineering teams. Nice-to-have qualifications: • Experience building agentic systems or LLM based workflows for automation. • Background in animation, simulation, robotics, video games, or interactive environments. • Experience with video generation, multi modal foundation models, diffusion models, world models, or generative models for 3D, 4D, motion, animation, or scene synthesis. • Experience with real time rendering, offline rendering, physics-based rendering, ray tracing, shader development, material systems, or rendering optimization. • Experience with large scale data generation systems, including distributed rendering, simulation orchestration, dataset versioning, automated quality checks, and human review tooling. • Research publications in computer graphics, computer vision, machine learning, robotics, or