Sr. Machine Learning Engineer 5

Our Company

Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. 

We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!

Senior Machine Learning Engineer - Agentic AI & Semantic Intelligence

Job Description Summary

Core Focus: Develops modern agentic AI systems, reinforcement learning algorithms for autonomous agents, and sophisticated semantic search solutions. Builds full-stack ML systems from research prototypes to production deployment, combining deep learning, reinforcement learning, and semantic understanding technologies.

Key Responsibilities: Architects and develop agentic AI systems that autonomously create and manage audiences, implements RL frameworks for agent decision-making, and builds semantic search engines with advanced intent classification. Creates end-to-end solutions from algorithm implementation to API design.

The Opportunity

Join Adobe's mission to revolutionize marketing automation through Agentic AI and Semantic Intelligence. We're building next-generation AI agents that autonomously understand marketer and user intent, make intelligent decisions about audience creation, and deliver personalized experiences through advanced semantic understanding.

As a Senior Machine Learning Engineer specializing in Agentic AI and Reinforcement Learning, you'll be the technical architect behind our autonomous audience agents, developing sophisticated RL algorithms and semantic search systems that seamlessly integrate these capabilities.

What You'll Do

Agentic AI & Reinforcement Learning

• Design and implement RL frameworks for autonomous audience agents using advanced algorithms (PPO, A3C, SAC)

• Develop multi-agent systems for collaborative audience creation and management tasks

• Build reward functions and training environments that learn from real marketing outcomes

• Architect agent systems (reactive, deliberative, hybrid) for real-world applications

Semantic Search & Intent Understanding

• Build semantic search engines using transformer models, vector databases, and dense retrieval systems

• Develop intent classification models that translate marketing queries into actionable audience definitions

• Create embedding pipelines for real-time semantic matching between user profiles and objectives

• Implement cross-encoder re-ranking systems for improved search relevance

Full-Stack Development & Research

• Design end-to-end ML pipelines from data ingestion through model serving, monitoring and retraining

• Build scalable APIs and microservices supporting real-time agent decision-making

• Stay at the forefront of agentic AI research, implementing modern techniques from academic literature

• Conduct applied research on novel RL formulations and semantic understanding techniques

What You Need to Succeed

Educational Requirements

• Ph.D. in AI, ML, Computer Science, or related field with 2+ years of agentic AI/RL experience, OR

• Master's degree with 5+ years building production ML systems focused on autonomous agents and semantic search

Core Technical Skills

Agentic AI & Reinforcement Learning:

• Expert experience with RL frameworks (Ray RLlib, Stable-Baselines3, OpenAI Gym)

• Deep understanding of RL algorithms: policy gradients, actor-critic methods, multi-agent RL

• Hands-on experience building autonomous agents for real-world applications

Semantic Search & NLP:

• Advanced expertise in transformer architectures, embedding models, and vector search

• Production experience with semantic search systems (FAISS, Milvus, similar vector DBs)

• Strong background in intent classification, BERT/sentence transformers, cross-encoder architectures

Full-Stack Development:

• Expert Python programming with proficiency in Go, or Rust, or Java