Machine Learning Engineer

Adobe
San Jose$162k – $234kPosted 28 April 2026

Job Description

Adobe Cloud is brimming with billions of pieces of rich content and ever growing on daily basis. The kind of content ranges from images, photos, vectors, brushes, videos, composites, text documents, 3D, and anything we could think of. Information retrieval is a critical part of this offering. Creative professionals and novice users alike need quick access to their digital assets, libraries, the variety of creative content, and documents they work with every day, from brushes to colors, images, videos and beyond. We have built a Search, Content & Discovery Platform that powers multiple Adobe product lines such as Adobe’s Creative Cloud product, Experience Cloud, Document Cloud, Lightroom and creative marketplace by enabling the world’s best creative tools, leading cloud services for managing creative assets, and the leading marketplace such as Adobe Stock. Search platform deals with billions of assets stored in cloud for variety of use cases ranging from privately accessible assets as in Lightroom, Creative cloud and others, shared assets via collaboration in creative cloud and experience cloud and public discoverable assets as in Adobe Stock Marketplace, Adobe.com , Adobe Learn & Tutorials content. What You’ll Do Develop and implement scalable, efficient, and modern algorithms that can work with large-scale data in production systems Work on large scale streaming and data systems to build world class search, recommendation and Gen AI systems Work closely with data scientists, AI models to take them to production, scale and make them efficient and reliable Collaborate with product management and engineering groups to develop new products and features. What You Need to Succeed BS/Advanced degree in quantitative fields: Computer Science, Data Science, AI/ML Engineering, or a related field Strong analytical and quantitative problem-solving ability. Proficient in one or more programming languages such as Python, Java Strong understanding and working knowledge of distributed systems, isolation and micro services Good understanding of machine learning, deep learning, or data analytics concepts. Excellent communication, relationship skills and a team player Become part of this growing team at Adobe and have a phenomenal impact by contributing to search, browse, machine learning and recommendation across the creative suites of products at Adobe. We match the pace, innovation and excitement of a startup, backed by the resources and infrastructure of Adobe! We’re looking for top notch technical contributor to deliver Search as the core tenet in Adobe Cloud. The work entails building large scale search indexing, Search algorithms, recommendation algorithms, relevance & ranking, visual search, data mining, machine learning, data analysis & metrics, query processing, multi-lingual search, search UX, and overall Adobe Cloud ecosystem. This is an opportunity to make a huge impact in a fast-paced environment at a great company. Join us! 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 ... (truncated, view full listing at source)
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