below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$200,437–$251,925.
Based on 240 similar postings.
Employer
About Adobe
Adobe Inc. is a global software company known for creative and multimedia software products including Photoshop, Illustrator, Acrobat, and its cloud-based Creative Cloud and Document Cloud suites. Industry: Creative & Digital Experience Software
Adobe currently has
282 open roles
on FindRole.
Listed pay typically runs
$148,100–$282,100
across 76 roles with salary data.
The Senior Machine Learning Engineer joins the Pro Design team to power intelligence within professional design tools like Illustrator and InDesign. This hands-on modeling role involves partnering with Product and Engineering teams to translate research into shipped experiences. You will design, prototype, and ship models for predictive, ranking, generative, and agentic systems, including RAG, embeddings, fine-tuning, and in-product copilots. Responsibilities include owning end-to-end evaluation, building MLOps foundations like feature pipelines and CI/CD, and monitoring production quality. The role requires proficiency in Python, SQL, and modern GenAI frameworks. You must possess a strong foundation in supervised and unsupervised models for personalization and recommendation. The work focuses on solving technical challenges in creative tools by building intelligent, connected systems for professional creators.
What does a Machine Learning Engineer earn in California?
Median $235750 from 200 postings across 34 companies.
Design, prototype, and ship models for predictive, ranking, generative, and agentic systems.
Implement RAG, embeddings, fine-tuning, and in-product copilots for creative use cases.
Define success metrics and build offline and online evaluation harnesses for production models.
Detect and resolve quality regressions in production environments.
Build MLOps foundations including feature pipelines, experiment tracking, versioning, and CI/CD.
Develop automated retraining and monitoring systems to ensure model reliability.
Translate research and technical problems into shipped product experiences.
What we're looking for
Bachelor's in a quantitative field (CS, ML, Data Science, Engineering, or similar) or equivalent practical experience.
5+ years of experience building, deploying, and operating ML systems in production at scale.
Strong core ML foundation in feature engineering and shipping supervised/unsupervised models for prediction, ranking, recommendation, or personalization.
Working depth in modern GenAI including LLMs, RAG, embeddings, fine-tuning, or agent design in production.
Fluency in Python and SQL, along with broader ML tooling and infrastructure ecosystem.
Experience with rigorous offline and online evaluation and experimentation design and operation.
Ability to frame problems before modeling and communicate technical work to non-technical partners.
Master's or PhD in a quantitative discipline (preferred).
Python
C++
PyTorch
CUDA
GPU Kernel Optimization
Distributed Training
Data Pipelines
Inference Serving
Computer Architecture
Model Deployment
Data Ingestion
Profiling
Debugging
Claude