Senior Machine Learning Engineer

Adobe

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: San Jose, CA
Salary: $183,300–$265,350 / yr
Posted: 116 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $220k

This role $224k

$169k most similar roles pay here $276k

This role pays more than 52% of similar roles. Most pay $184,625–$254,750 — the shaded band above. At the midpoint, this role pays about $224k versus about $220k 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 218 open roles on FindRole.

Listed pay typically runs $187,100–$270,950 across 216 roles with salary data.

Most-posted roles

View all roles at Adobe

At a glance

TL;DR · Senior Machine Learning Engineer

Role Posting Log in to save

Senior Machine Learning Engineer The Senior Machine Learning Engineer joins the Agent Platform team within Adobe Experience Platform to build a production-grade infrastructure for autonomous AI agents. This role involves developing core agent runtime, tool execution layers, memory systems, and sandboxed execution environments while managing high-throughput inference pipelines and cost-aware model routing. The engineer will design ML workflows for model customization, serving, and lifecycle management to support diverse customer workloads. Required skills include a Master’s or PhD in Computer Science, five years of experience building production ML systems, and proficiency in Python or Java. Candidates must have hands-on experience with PyTorch, TensorFlow, or JAX, along with expertise in LLM prompt engineering, fine-tuning, and cloud platforms like AWS or Azure. The role addresses the technical challenge of creating a multi-tenant Agent-Ops stack that provides reliable, scalable orchestration for enterprise-level marketing applications.

What does a Machine Learning Engineer earn in California?

Median $246394 from 172 postings across 28 companies.

See salary data

Skills

Python Java PyTorch TensorFlow JAX LLMs RAG AWS Azure Redis Elasticsearch Snowflake Microservices ML-Ops Agent-Ops Monitoring Observability

What you'll do

Build core agent infrastructure including runtime systems, tool execution layers, and memory management.
Develop high-throughput inference pipelines with sub-second orchestration latency and cost-aware model routing.
Design and implement systems for model customization, serving, and lifecycle management at enterprise scale.
Prototype and experiment with new approaches to agent reasoning, tool orchestration, and evaluation methods.
Manage the full production lifecycle including deployment, monitoring, observability, and incident response.
Translate customer feedback and real-world performance data into technical product roadmap improvements.

What we're looking for

Ph.D. or M.S. in Computer Science or a related field is required.
5+ years of experience building and deploying production ML systems for large-scale users is required.
Proficiency in Python and/or Java with experience designing APIs and microservices is required.
Hands-on experience with at least one modern deep learning framework like PyTorch, TensorFlow, or JAX is required.
Production experience with LLMs including prompt engineering, fine-tuning, and building LLM-powered applications is required.
Experience with cloud platforms (AWS or Azure) and data infrastructure such as Postgres, Redis, or Snowflake is required.
Ability to own production systems end-to-end, including deployment, monitoring, and incident response, is required.
Strong communication skills and the ability to influence technical decisions in a collaborative environment are required.