Staff ML Engineer: Multimodal Retrieval & Ranking

Adobe; San Jose (CA); On-site; USD 212,000 - 307,000; Full time

Job summary

Adobe is seeking a Staff Machine Learning Engineer to design and deploy semantic matching, retrieval and ranking models across multimodal content. You will build representation learning systems with LLMs and vision-language models and scale architectures for search, recommendations, and discovery across Adobe products.

You’ll train, fine-tune, and optimize models on large datasets, create rigorous evaluation plans, and partner with research and product teams to drive end-to-end ML lifecycle and

Qualifications

• Experience building production ML systems.
• Experience with retrieval, ranking or semantic matching at scale.
• Knowledge of representation learning and transformer models.
• Experience with multimodal models (text/images/docs).

Responsibilities

• Design and deploy semantic matching and ranking models for multimodal content.
• Develop representation learning systems using LLMs and vision-language models.
• Build scalable retrieval architectures for search, recommendations and discovery.
• Train, fine-tune, and optimize ML models on large datasets.
• Create evaluation benchmarks and experiments to measure relevance and impact.
• Collaborate with research, product and engineering to ship production features.
• Lead end-to-end ML lifecycle from data prep to deployment and monitoring.
• Stay ahead on advances in IR, multimodal AI and agentic systems.

Skills

Semantic matching

Retrieval systems

Multimodal ML

LLMs

Python

PyTorch

TensorFlow/JAX

MLOps

A/B testing

Distributed training

Education

MS or PhD in Computer Science or ML

Tools

PyTorch

TensorFlow

JAX

Hugging Face

Ray

Spark

Job description

Adobe is seeking a Staff Machine Learning Engineer to design and deploy semantic matching, retrieval and ranking models across multimodal content. You will build representation learning systems with LLMs and vision-language models and scale architectures for search, recommendations, and discovery across Adobe products.

You’ll train, fine-tune, and optimize models on large datasets, create rigorous evaluation plans, and partner with research and product teams to drive end-to-end ML lifecycle and