Machine Learning Engineer 4

Adobe
San Jose$183k – $265kPosted 2 May 2026

Job Description

The Opportunity Adobe is looking for a Senior Machine Learning Engineer to help shape the future of agentic AI in the enterprise. In this role, you will design, build, and scale cutting-edge platforms and products that redefine how enterprises create and optimize customer experiences and marketing campaigns. You will play a key role in advancing  AEP Agent Orchestrator —a foundational platform layer that manages and connects Adobe and third-party agents. You will work in a fast-moving, high-impact environment with a team of talent engineers and applied scientists where creativity, collaboration, and data-driven innovation come together to make a real difference. What you'll do Design and d evelopment of state-of-the-art agentic AI system and platform powered by generative AI, including working on engineering problems such as defining APIs, integrating with UIs, deploying Cloud services, CICD, etc., as well as implementing ML- and LLM-Ops best practices, delivering high quality, production ready code. Design and build ML workflows for enterprise-scale model customization, serving, and ecosystem integration. Partner with researchers and applied scientists on productization of innovations Engage in the product lifecycle, design, deployment, and production operations. What you need to succeed The ideal candidate will have the following background: PhD or MS degree in Computer Science or related field required. 5 years of experience in machine learning, including production-scale deployments Experience with agile development, and short release cycles Good understanding of statistical modeling, machine learning, or analytics concepts; ability to quickly learn new skills and work in a fast-paced team. Proficient in one or more programming languages such as Python and Java. Familiarity with cloud development on Azure/AWS. Experience using Relational (MySQL, Postgres) and NoSQL datastores (Redis, ElasticSearch, Snowflake) along with data access patterns and strategies Experience working with at least one deep learning framework such as TensorFlow or PyTorch. Experience with LLMs including prompt/context-engineering, modern LLM APIs, fine-tuning models etc. Experience working with both research and product teams. Excellent problem-solving and analytic skills Excellent communication and relationship building skills. About Adobe Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe’s industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity. Our 30,000 employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We’re on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours. Let’s Adobe together At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture , focus on people, purpose and community , Adobe for All , comprehensive benefits programs , the stories we tell , the customers we serve, and how you can help us advance our mission of empowering everyone to create. 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. Learn more. Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability o ... (truncated, view full listing at source)
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