Sr. Machine Learning Engineer 4

Adobe

Quick summary

Work type: On-site
Location: San JoseSeattle, WA
Salary: $183,300–$265,350 / yr
Posted: 1 day ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $222k

This role $224k

$165k most similar roles pay here $277k

This role pays more than 52% of similar roles. Most pay $195,000–$249,750 — the shaded band above. At the midpoint, this role pays about $224k versus about $222k for comparable roles.

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 325 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 325 roles with salary data.

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At a glance

TL;DR · Sr. Machine Learning Engineer 4

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As a Senior Machine Learning Engineer, you will join a dynamic team of engineers focused on developing and deploying cutting-edge ML and GenAI solutions. Your responsibilities include designing backend services for AI features, evaluating and deploying models using classical and deep learning techniques, and contributing to agentic systems that enable intelligent task automation. You will work closely with cross-functional teams to integrate these solutions into production workflows while continuously improving their efficiency and scalability. Essential skills include strong Python engineering capabilities, experience in MLOps, and familiarity with cloud platforms for scalable deployments. Ideal candidates have a Master’s or Ph.D. in Computer Science or related fields, along with hands-on experience in deploying ML models and mentoring junior engineers. This role offers opportunities to experiment with new technologies and contribute to high-impact projects within the rapidly evolving AI landscape at Adobe.

Skills

Python AWS GCP Azure MLOps CI/CD Docker Kubernetes Prometheus Terraform PostgreSQL Redis Git Jenkins TensorFlow PyTorch RAG LLM-as-a-judge NLP Agentic systems Multi-agent orchestration

What you'll do

Design and optimize backend services for ML and Generative AI features.
Develop, evaluate, and deploy various types of ML models in production.
Contribute to agentic systems and orchestration frameworks for task automation.
Analyze and improve the efficiency and scalability of AI-enabled systems.
Stay updated with advancements in ML, GenAI, and prompt optimization research.

What we're looking for

Master’s or Ph.D. in Computer Science, Machine Learning, or related field.
5+ years of experience in machine learning engineering and production ML systems.
Strong Python skills with expertise in system design and cloud platform deployment.
Experience deploying and monitoring ML models in production environments.
Hands-on involvement in agentic architectures and multi-agent orchestration systems.

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