Adobe
Principal Scientist - Data Pipeline Engineer
$206K–$388K
San Jose +2 · Principal · Full-time · Posted Oct 9, 2026
- Location
- San Jose
Seattle
San Francisco - Experience
- 10+ years in ML systems, ML infrastructure, or applied ML engineering, including work at billions-of-assets scale.
- Education
- Bachelor's, Master's, or Ph.D. in CS, Engineering, ML, or a related field.
About the job
Optimizes the cost, throughput, and quality of large-scale multimodal ML data pipelines that prepare assets for model training.
What you'll do
- Reduce end-to-end pipeline costs and improve throughput through DAG optimization, model and inference efficiencies, and data selection.
- Build evaluations and data curation methods that maintain training-data quality while improving efficiency.
- Partner with modeling and data platform teams on training outcomes, orchestration, scheduling, and storage.
What they ask for
- 10+ years in ML systems, ML infrastructure, or applied ML engineering, including work at billions-of-assets scale.
- Track record of reducing costs in large-scale ML data pipelines across compute, storage, and data access.
- Expertise optimizing inference for VLMs, LLMs, or other large models, including batching, quantization, serving, and distillation.
- Experience with generative or multimodal training-data curation and quality; strong Python and a systems-level language, plus distributed frameworks such as Ray or Spark.
Pay
$206,300 - $388,000 annually USD (base salary); $268,000 - $388,000 USD (base salary, California); $247,200 - $357,900 USD (base salary, Washington)
Tools
Python, C++, Rust, Go, Java, Ray, Spark
AI focus
Improves the cost and throughput of pipelines for image, video, and audio foundation models; optimizes and distills models, and curates and evaluates training data for LLMs, VLMs, and diffusion models.
Model-written summary · the original posting is authoritative