Lead Applied Researcher

Adobe; San Jose (CA); On-site; USD 120,000 - 150,000; Full time

Job summary

Adobe in San Jose is seeking an Applied Researcher for AI Foundations to develop innovative machine learning models across generative AI scenarios. The ideal candidate possesses a Master's or PhD in a related field, strong programming skills in Python, and proficiency in ML frameworks like PyTorch and TensorFlow.

You'll have the opportunity to drive AI research into production, collaborate with various teams, and make a significant impact in the field. Join Adobe to help shape the future of creative solutions powered by AI.

Qualifications

• Strong programming skills in Python and proficiency in ML frameworks.
• Experience with modern ML architectures including transformers and GANs.
• Ability to quickly read and prototype research papers.

Responsibilities

• Build innovative machine learning models for generative AI scenarios.
• Collaborate with teams to bring AI-powered features to life.
• Drive the end-to-end ML lifecycle from experimentation to production.

Skills

Machine learning

Programming (Python)

Computer vision

Natural Language Processing

MLOps

Education

Masters or PhD in a relevant field

Tools

PyTorch

TensorFlow

JAX

Job description

Applied Researcher, AI Foundations – Adobe Express

Adobe Express empowers users to seamlessly construct striking designs, whether novices or experienced engineers, on a user-friendly platform enhanced by groundbreaking AI capabilities. The AI Foundations team drives innovation to make Adobe Express smarter, faster, and more adaptive by developing modular, reusable AI systems and crafting a robust Horizon AI Stack.

Responsibilities

• Build innovative machine learning models that drive Agentic and other generative AI scenarios for Adobe Express.
• Develop and deploy advanced ML models in areas such as computer vision, NLP, and multimodal learning.
• Contribute to foundational AI systems for intelligent assistance, layout automation, image generation, and motion storytelling.
• Design and build modular ML components that integrate into Adobe’s Horizon AI Stack and serve multiple creative workflows.
• Drive the end‑to‑end ML lifecycle—from experimentation to evaluation, optimization, and production deployment.
• Collaborate closely with Adobe Research, engineering, and product teams to bring AI‑powered features to life.
• Design evaluation strategies using automated metrics, LLM‑based judges, and user feedback.

Basic Qualifications

• Masters or PhD (preferred) in Computer Science, Computer Engineering, Data Science, Machine Learning, or a related field with equivalent experience.
• Strong programming skills and proficiency in ML frameworks such as PyTorch, TensorFlow, or JAX.
• Experience with modern ML architectures including transformers / visual transformers, diffusion models, or GANs.
• Experience with cloud platforms, MLOps, and deploying ML systems in production at scale.
• Ability to quickly read, understand, and prototype relevant research papers.

Preferred Qualifications

• Experience with large language models and model adaptation techniques (e.g., PEFT, SFT, RL).
• Familiarity with agent‑based systems, intelligent assistants, or planner‑based AI.
• Experience in creative, imaging, or multimedia domains.
• Publications in renowned ML/CV/AI conferences such as NeurIPS, CVPR, ICML, or SIGGRAPH.

What You Need to Succeed

• Passion for creativity and learning with a drive to improve solutions.
• Up-to-date knowledge of the latest AI research.
• Comfortable working in a fast, iterative, and ambiguous environment.
• Strong communication skills with the ability to explain technical ideas and experimental results clearly.
• Collaborative spirit with a focus on product impact, AI/ML innovation, and engineering excellence.

Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic.