Senior Machine Learning Engineer

Adobe•San Jose, CA

About The Position

As a Senior Machine Learning Engineer with Adobe's Experience Intelligence team, you will compose, build, and deploy production-grade AI systems. These systems power intelligent experiences across commercial and promotional activities. You will work on GenAI agents, predictive ML, retrieval and reasoning systems, and the platforms that support them at scale. Partnering with engineers, product managers, and business collaborators, you will turn emerging AI capabilities into reliable, scalable solutions that solve real-world business problems.

Requirements

MS or PhD in Computer Science, Machine Learning, or a related field, or equivalent practical experience.
5+ years of experience building and deploying machine learning, GenAI, NLP, retrieval, or related AI systems.
Strong understanding of modern LLM and agentic AI technologies, including RAG, tool/function calling, reasoning, evaluation, and context management.
Strong foundation in machine learning, predictive modeling, statistics, and techniques for working with large-scale structured and unstructured data.
Strong software engineering skills, including Python, data structures and algorithms, system design, testing, code quality, and production debugging.
Experience building production AI/ML services using technologies such as PyTorch, REST APIs, Docker, data/orchestration pipelines, and cloud platforms such as Azure or AWS.
Experience designing scalable and reliable AI systems and evaluating them across quality, latency, cost, and operational performance.
Excellent problem-solving and communication skills, with the ability to work effectively across technical and business teams in a fast-paced environment.

Responsibilities

Design, build, and deploy production-grade AI systems, including GenAI agents, predictive ML, retrieval and reasoning systems, agent frameworks, tool calling, multi-agent workflows, APIs, and data pipelines, with a strong focus on quality, scalability, reliability, and performance.
Develop AI/ML solutions over large-scale structured and unstructured enterprise data, including evaluation frameworks and techniques to continuously improve accuracy and user experience.
Own solutions end-to-end, from architecture and experimentation through implementation, testing, deployment, monitoring, and continuous improvement.
Partner closely with product managers and collaborators to identify high-value problems and integrate AI capabilities into real-world sales and marketing workflows.
Identify and prototype emerging AI opportunities, turning new technologies and ideas into differentiated, production-ready capabilities.