Staff Machine Learning Engineer

Adobe

Quick summary

Work type
On-site
Location
San Jose, CA
Salary
$211,800–$306,625 / yr
Posted
2 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $222k
This role $259k
$166k most similar roles pay here $322k

This role pays more than 80% of similar roles. Most pay $193,750–$249,750 — the shaded band above. At the midpoint, this role pays about $259k 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 301 open roles on FindRole.

Listed pay typically runs $183,300–$265,350 across 299 roles with salary data.

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At a glance

TL;DR · Staff Machine Learning Engineer

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As a Staff Machine Learning Engineer (MLE 50) on Adobe's AI Foundations team within the Search, Discovery & Content AI organization, you will design and deploy semantic matching and ranking models that understand various content modalities at scale. Your daily tasks include building representation learning systems using large-scale datasets to enhance relevance and content understanding across Adobe’s products like Acrobat, Adobe Stock, Lightroom, and Creative Cloud. You’ll develop scalable retrieval and ranking architectures for search, recommendation, and agentic workflows, and work closely with research teams to translate cutting-edge AI innovations into production capabilities. Essential skills include expertise in machine learning techniques such as transformer architectures and multi-objective optimization, proficiency in Python and modern ML frameworks like PyTorch or TensorFlow, and experience with distributed training and MLOps methodologies.

Skills

Python PyTorch TensorFlow JAX Hugging Face Ray Spark MLOps LLMs Vision-Language Models Multimodal Foundation Models Distributed Training Large-Scale Data Processing A/B Testing Relevance Metrics Learning-to-Rank Vector Search Embedding-Based Retrieval Approximate Nearest Neighbor Systems

What you'll do

  • Design and deploy semantic matching, retrieval, and multi-objective ranking models for multimodal content.
  • Build representation learning systems using LLMs, vision-language models, and embedding models to enhance content understanding.
  • Develop scalable retrieval and ranking architectures for search, recommendation, and agentic workflows across Adobe's ecosystem.
  • Train, fine-tune, and optimize machine learning models with large-scale datasets for improved performance.
  • Create evaluation frameworks and benchmarks to measure the effectiveness of ML systems in user impact.

What we're looking for

  • Strong experience building and deploying machine learning systems in production.
  • Deep understanding of modern ML techniques, including representation learning and transformer architectures.
  • Experience developing retrieval, recommendation, ranking, or semantic matching systems at scale.
  • Proficiency in Python and expertise with modern ML frameworks like PyTorch or TensorFlow.
  • Ability to design and analyze offline and online evaluations for machine learning models.
  • Strong software engineering skills and familiarity with distributed training and MLOps methodologies.
  • MS or PhD in Computer Science, Machine Learning, Artificial Intelligence, or related field.

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