Machine Learning Engineer at Adobe

Department: Engineering and Product

Compensation

$133,100 – $236,400/yr

Setup: On-site
Location: San Francisco, California
Type: Full-time
Level: senior
Posted: Sep 15, 2026

Description

Adobe is hiring a Senior Machine Learning Engineer to build and operate machine learning systems for its creative products. The role covers full-stack modeling across predictive, ranking, generative, and agentic systems, including RAG, embeddings, fine-tuning, and in-product copilots; end-to-end evaluation; and MLOps foundations such as feature pipelines, experiment tracking, versioning, CI/CD, automated retraining, and monitoring. Candidates need a quantitative bachelor's degree or equivalent experience, at least five years of production ML systems experience, strong core machine learning and modern generative AI skills, Python and SQL fluency, and experience with offline and online evaluation. The U.S. pay range is $133,100 to $236,400 annually.

Required Skills

Feature engineering
LLMs
RAG
Python
SQL
MLOps
Experimentation

Additional Information

Minimum Education: Bachelor's degree in a quantitative field such as computer science, machine learning, data science, or engineering, or equivalent practical experience.
Required Previous Experiences: At least 5 years building, deploying, and operating machine learning systems in production at scale.
Experience shipping supervised and unsupervised machine learning models for prediction, ranking, recommendation, or personalization.
Experience with LLMs or generative models in production, including RAG, embeddings, fine-tuning, or agent design.
Experience with Python, SQL, and machine learning tooling and infrastructure.
Experience designing and operating offline and online evaluation and experimentation.
Preferred Qualifications: Master's or PhD in a quantitative discipline.
Background in consumer product analytics, especially in creative tools, SaaS, or subscription businesses.
Experience with recommendation systems or personalization for visual or creative content.
Experience deploying and monitoring models in Databricks or a comparable production machine learning environment.