Senior ML Infrastructure Engineer

Adobe; San Jose (CA); On-site; USD 183,000 - 265,000; Full time

Job summary

Adobe is seeking a Senior Machine Learning Engineer to join the Applied Science Data Frameworks team in California. You will help build foundational infrastructure powering multimodal AI training and inference, shipping data loaders, feature enrichment pipelines, and dataset management for petabyte-scale models.

You will work with distributed data loading for PyTorch, batch inference, and semantic search infrastructure across GPU clusters, contributing to scalable ML data pipelines and

Qualifications

• 5-6 years of professional experience building and operating distributed systems in production.
• Strong understanding of distributed computing concepts with Spark, Ray, Dask, or equivalent.
• Familiarity with cloud platforms (AWS or Azure) and data platforms such as Databricks or Spark.
• Proficiency in Python and software engineering fundamentals—system design, data structures, algorithms.
• Familiarity with ML frameworks such as PyTorch or TensorFlow; hands-on ML experience is a plus.
• Basic familiarity with MLOps practices including CI/CD pipelines, Docker, and deployment automation.
• Bachelor's degree in CS/Engineering; MS is a plus.
• Strong communication skills and ability to collaborate across teams.

Responsibilities

• Build and maintain distributed training data loaders for multi-source data ingestion and real-time transforms.
• Develop feature enrichment pipelines and dataset registry for multimodal model training.
• Create batch inference pipelines for large-scale feature extraction and GPU cluster processing.
• Develop data processing systems using Spark, Ray, and SQL-based ingestion; use Apache Arrow storage.
• Support semantic search and vector databases (OpenSearch/LanceDB) for dataset discovery.
• Contribute to CI/CD for ML systems, including self-hosted runners and Docker-based automation.
• Collaborate with ML researchers to translate training needs into scalable data loading infrastructure.
• Write reusable framework components and SDKs to accelerate platform adoption across teams.
• Optimize pipelines for latency, throughput, memory, and GPU utilization.
• Improve observability and reliability for 24/7 training workloads.

Skills

Distributed systems

Python

PyTorch

TensorFlow

Apache Spark

Docker

MLOps

Education

Bachelor's degree in Computer Science or Engineering

MS is a plus

Tools

OpenSearch

LanceDB

SQL-based data ingestion

Apache Arrow

Databricks

Docker

Job description

Adobe is seeking a Senior Machine Learning Engineer to join the Applied Science Data Frameworks team in California. You will help build foundational infrastructure powering multimodal AI training and inference, shipping data loaders, feature enrichment pipelines, and dataset management for petabyte-scale models.

You will work with distributed data loading for PyTorch, batch inference, and semantic search infrastructure across GPU clusters, contributing to scalable ML data pipelines and