> Markdown version of [/jobs/ext/2514391-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2514391-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer

- **Company:** Adobe Systems
- **Location:** United States
- **Experience:** Expert
- **Salary:** $238,700.0 - $345,650.0
- **Contract:** Permanent contract
- **Skills:** Adobe Acrobat, Adobe Photoshop, Adobe Creative Cloud, Adobe Photoshop Lightroom, Artificial Intelligence, Cloud Computing, Data Structures, Cursor (Graphical User Interface Elements), Programming Tools, Machine Learning, Language Modeling, Systems Development Life Cycle, Software Engineering, Systems Architecture, Pytorch, Large Language Models, Multi-Agent Systems, Generative AI, Adobe, Information Technology
- **Published:** August 9, 2026
- **Apply:** https://www.careerbuilder.com/job-details/staff-agentic-ml-engineer-photoshop-waltham-ma--0e0046d3-7500-4ce1-b5c5-faefcd4a330f

## About the Role

* 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
 * Experience with multimodal models (vision-language, image generation/editing) is a strong plus, Adobe Acrobat, Adobe Photoshop, Adobe Product Family, Algorithms, Architectural Services, Artificial Intelligence (AI), Artificial Intelligence (AI) Agents, Benchmarking, Best Practices, Cloud Computing, Communication Skills, Compensation and Benefits, Computer Science, Customer Experience, Data Science, Data Structures, Ecosystems, Image Manipulation, Leadership, MCP - Microsoft Certified Professional, Machine Learning, Mentoring, Modeling Languages, Multimodal Interaction, Problem Solving Skills, Production Systems, Programming Tools, Quality Metrics, Safety/Work Safety, Sales, Sales Commission, Software Engineering, System Architecture

## Description

We are building an advanced AI platform that powers next-generation creative workflows for flagship products like Photoshop and Lightroom. As a Senior Machine Learning Engineer (or Applied Scientist), you will combine deep technical expertise with architectural leadership to design and implement reasoning systems, tool orchestration, and multimodal integrations using cutting-edge large language models (LLMs) and vision-language models (VLLMs).

The Opportunity

 * (M)LLM post-training and evaluation, including fine-tuning, alignment, and domain adaptation
 * Agent system architecture design and implementation at scale
 * Practical agent development using frameworks such as LangChain, LangGraph, MCP, and A2A
 * Image generation and editing with multimodal AI
 * Building and owning rigorous evaluation frameworks for LLM and agent performance

What You'll Do

 * 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
 * Move fast in an environment where priorities evolve and problems are sometimes loosely defined


## Related Videos

- [3x Performance: A Humbling Journey](https://www.wearedevelopers.com/videos/100165-3x-performance-a-humbling-journey)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development)
- [NoCode LiveCode: Leveraging AI Tools to Craft Fully Functional Apps!](https://www.wearedevelopers.com/videos/1169-nocode-livecode-leveraging-ai-tools-to-craft-fully-functional-apps)
- [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)

## Related Articles

- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)
- [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path)
- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)