Applied Scientist

Adobe•San Jose, CA

9h•Remote

About The Position

The Adobe Experience Intelligence Team is seeking an Applied Scientist to build, deploy, and scale AI-powered systems that drive measurable business impact across Adobe's products. This role involves leveraging AI, including AI-assisted coding and rapid prototyping, to build end-to-end products that solve real business problems. The ideal candidate is a strong engineer who uses AI to multiply their output, comfortable with rapid prototyping and designing scalable production systems. Responsibilities include building RAG pipelines, standing up web apps, writing data pipelines in Spark, and deploying services on cloud infrastructure, all while utilizing AI coding tools for increased efficiency.

Requirements

MS or PhD in Computer Science, Statistics, Machine Learning, or related fields, or equivalent experience; or BS with equivalent practical experience
Experience building ML/AI systems, with a track record of shipping models or AI applications to production
Strong programming skills in Python
Proficiency with AI-assisted coding tools (e.g., Claude Code, GitHub Copilot, Cursor) and a demonstrated ability to use them to rapidly build full-stack applications
Hands-on experience with LLMs, including prompt engineering, RAG, or building AI agents
Experience with cloud platforms (Azure preferred, or AWS/GCP) and big data tools (Spark, Databricks)
Solid foundation in machine learning, deep learning, and statistical modeling
Strong analytical and quantitative problem-solving ability
Excellent communication and collaboration skills; ability to work directly with non-technical business collaborators

Nice To Haves

Experience building autonomous AI agents, multi-agent systems, or agentic workflows that orchestrate tools and APIs to complete complex tasks
Experience with function calling and tool-use patterns for connecting LLMs to external systems, databases, and data sources
Experience with evaluation and observability for AI systems — building evals, monitoring hallucinations, measuring output quality at scale
Track record of using AI-assisted coding to rapidly ship production applications (e.g., building a working product in days, not months)

Responsibilities

Rapidly build end-to-end AI products — from idea to deployed application — using AI-assisted coding tools to accelerate development across the full stack (frontend, backend, data, infrastructure)
Build and deploy GenAI applications — including LLM-powered agents, RAG systems, and AI assistants — to solve real business problems such as business intelligence, workflow automation, and Q&A over structured and unstructured data
Build and maintain scalable ML/AI pipelines on cloud infrastructure (Azure, Databricks) that process large-scale user behavioral data
Collaborate directly with business collaborators across Adobe to identify high-impact AI opportunities, prototype solutions quickly, and deliver measurable results
Own end-to-end delivery of AI services — from data ingestion and model training to API development, UI, deployment, monitoring, and business impact measurement