Jobs / United States / Adobe INC
Principal Scientist - Data Pipeline 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).
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.
Or apply yourself on the official page →
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
ABOUT THE ROLE We’re looking for a Pr incipal ML Engineer to architect and scale the multimodal data processing pipelines and infrastructure behind Adobe Firefly’s multimodal foundation models (image, video, audio). In this role, you’ll sit at the intersection of data engineering and applied ML building distributed, GPU-accelerated systems that turn billions of raw assets into training-ready data at scale. Your wor k will directly determine how fast and how well Adobe models can learn directly impacted by the throughput and reliability of our data pipelines , and the quality of data that reaches training. This is a senior individual contributor role with broad technical influence across data, infrastructure, and modeling teams. WHAT YOU’LL DO OPTIMIZE DATA PROCESSING PIPELINES AT SCALE • Architect and optimize large-scale distributed pipelines that process billions of images, video, and audio assets through ML workflows into training-ready data • Scale up inference throughput across the pipeline ( batching, parallelism, hardware utilization ) to turn raw collected data into training data faster and more cheaply • Identify and eliminate bottlenecks across ingestion, processing, and delivery, from storage and I/O to compute scheduling ARCHITECT SCALABLE DATA INFRASTRUCTURE • Design systems that reliably store, index, and serve billions of data points, each requiring substantial processing spanning large-scale databases, distributed storage, and high-throughput compute • Apply deep expertise in distributed systems and frameworks such as Ray (or equivalent) to orchestrate large-scale, GPU /CPU -heavy data workloads • Own architecture decisions including database and storage choices, job scheduling, GPU cluster utilization that let the platform scale alongside data and model growth DRIVE DATA CURATION FOR MODEL TRAINING • Bring a strong ML background , especially inference optimization for VLMs and LLMs and data curation for training • Partner closely with modeling teams to understand what data improves training outcomes, and translate that into pipeline and curation requirements • Operate as a hands-on technical leader who bridges data engineering and applied ML WHAT YOU NEED TO SUCCEED • 10+ years of experience in data engineering, ML infrastructure, or distributed systems, including work at large scale (billions of records or assets) • Strong software engineering background, with hands-on expertise in distributed systems and frameworks such as Ray, Spark, or equivalent large-scale data processing frameworks • Proficiency in Python, plus strong experience in a systems-level language (C++, Rust, Go, or Java) with strong debugging skills across distributed and ML-centric runtime environments. • Deep knowledge of databases and storage systems at scale such as data lakes, indexing, and retrieval across billions of data points • Strong ML background, particularly exper tis e in optimizing GPU inference pipelines for VLMs, LLMs, or other large models (batching, quantization, serving, throughput/latency tradeoffs) • Experience with data curation for model training : understanding what makes data valuable for training generative or multimodal models, not just how to move it efficiently • Comfort operating across the full stack, from low-level systems and GPU optimization to higher-level data strategy and curation decisions • Ability to communicate clearly and partner effectively across data, infrastructure, and modeling teams • Bachelor’s, Master’s, or Ph.D. in Computer Science, Engineering, Machine Learning, or a related field About Adobe Adobe empowers