Staff Agentic ML Engineer - Photoshop

Adobe
San Jose, California, United States of America / Waltham, Massachusetts, United States of America / San Francisco, California, United States of America2026-06-17Full time

About the job

Exciting opportunity for a Staff Machine Learning Engineer to lead the development of next-generation AI agents for flagship Photoshop and Lightroom products. Drive architectural innovation, mentor engineers, and shape the future of creative workflows using LLMs and multimodal AI. Join us to make a real impact in the AI platform space.

Responsibilities

Lead the development of next-generation AI agents that improve and extend Adobe's product ecosystem

Drive the architecture and implementation of robust agentic systems that combine reasoning, retrieval, tool use, and multimodal capabilities

Own end-to-end LLM fine-tuning pipelines — data curation, training, RLHF/DPO alignment, and evaluation

Design and maintain comprehensive evaluation frameworks to measure agent quality, reliability, and safety

Implement state-of-the-art LLM techniques for specialized creative applications

Mentor and grow engineers and scientists across the team; establish technical best practices

Qualifications

Minimum

Master's or Ph.D. in Computer Science, Machine Learning, Data Science, or a related field

8+ years of industry ML experience

Demonstrated expertise in LLMs, fine-tuning (SFT, RLHF, DPO, PEFT/LoRA), and agentic system development in production

Deep experience building evaluation frameworks for LLM and multi-agent systems (LLM-as-judge, automated benchmarks, red-teaming)

Proficiency in PyTorch and agentic frameworks: LangChain, LangGraph, MCP, Agent Development Kit (ADK)

Fluency with AI-assisted development tools (e.g. Claude Code, Codex, Cursor) while maintaining independent engineering judgment and critical ownership of technical decisions

Strong foundation in data structures, algorithms, and software engineering principles

Excellent problem-solving and communication skills; comfortable operating in fast-moving, ambiguous environments

Preferred

Experience with multimodal models (vision-language, image generation/editing)