Machine Learning Engineer

The Challenge

Search, Discovery, and Content AI (SDC) is a cornerstone of Adobe's ecosystem, enabling creative professionals and everyday users to access, discover, and work with a wide array of digital assets and creative content - including images, videos, documents, vector graphics, brushes, colors, and more. Users need quick access to what they've built, what has been shared with them, and what's available across marketplaces like Adobe Stock. With increasing demand for intuitive search, contextual discovery, and seamless content interactions across Adobe products like Firefly, Acrobat, Lightroom, Express and Adobe Stock, SDC is evolving into a Generative AI powerhouse.

At the heart of this work is the Content Processing Framework (CPF), a unified Agentic platform for efficient, reliable, and scalable content processing - both ML and non-ML - across all Adobe content. It is the backbone of Intelligent Content Processing within Adobe offerings, supporting hundreds of applied researchers, millions of end customers, and billions of content pieces that power our customers' entire digital journey.

This team develops innovative solutions for Intent understanding, personalized recommendations, and action orchestration to transform how users interact with Content. Working with extensive datasets and pioneering technologies, you will help redefine the discovery experience and drive user success. We match the pace, innovation, and excitement typical of new enterprises, backed by the resources and infrastructure of Adobe. If working at the intersection of machine learning, generative AI, and real-time systems excites you, we'd love to have you join us.

Responsibilities

As a Machine Learning Engineer on the SDC team, you will develop and optimize machine learning models and algorithms for search, recommendation, and content understanding across diverse content types. You will build and deploy scalable generative AI solutions. These will enable intelligent content discovery and contextual recommendations within Adobe products. This includes Firefly, the Creative Cloud suite, Document Cloud, and Marketing Cloud.

Your work will involve extensive data handling, data ingestion, search indexing, analytics, and distributed computing - building platforms that index billions of images, documents, and other assets in real-time. You will apply analytics and machine learning to improve ranking and recommendations within the search workflow, maintain and enhance the search engine, and develop new features using technologies such as Elastic Search, REST web services, SQS/Kafka, Hadoop, and deep learning.

Working alongside multi-functional groups, you will integrate ML models into production systems, ensuring high performance, reliability, and user impact. Your role will involve researching, crafting, and implementing groundbreaking techniques in language comprehension, computer vision, and multimodal learning for content and asset discovery. You will contribute to the end-to-end ML pipeline - including data preprocessing, model training, evaluation, deployment, and monitoring - while pushing the boundaries of computational efficiency to meet the needs of real-time, large-scale applications. Partnering with product teams, you will identify customer needs and translate them into innovative solutions that prioritize usability and performance. Additionally, you will mentor and provide technical guidance to junior engineers and multi-functional collaborators, driving excellence and innovation within the team.

What You'll Need to Succeed

- Bachelor's or equivalent experience; advanced degree such as a Ph.D. in Computer Science, Machine Learning, Data Science, or a related field is preferred.

- 6-9 years of industry experience building and deploying machine learning systems at scale.

- Experience engineering SaaS-based software.

- Proficiency in programming languages such as Python (for ML/AI) and Java (good to have for production-grade systems).

- Strong expertise in machine learning frameworks and tools (e.g., TensorFlow, PyTorch).

- Solid understanding of mathematics and ML fundamentals: linear algebra, statistics, optimization, and numerical methods.

- Experience with deep learning techniques for computer vision (e.g., CNNs, transformers), natural language understanding (e.g., BERT, GPT), or multimodal AI.

- Consistent track record of delivering ML solutions to production environments, optimizing performance, and ensuring reliability.

- Practical experience processing data at a large scale.

- Experience with AWS resources.

- Experience with search engine technology.

- Knowledge of large-scale distributed systems and frameworks (e.g., Kubernetes, Spark, Hadoop).

- Strong problem-solving skills and the ability to innovate new solutions for complex challenges.

- Excellent communication and collaboration skills to work efficiently in a fast-paced, multi-functional environment.

Nice-to-Haves

- Experience with generative AI (e.g., Stable Diffusion, DALL·E, Midjourney) and its application in content creation or discovery.

- Experience with Elastic Search/Solr and building indexing pipelines.

- Knowledge of computational geometry, 3D modeling, or animation pipelines.

- Familiarity with real-time recommendation systems or search indexing.

- Publications in peer-reviewed journals or conferences in relevant fields.

- Experience with Web services and REST.

- Experience with RDBMS and NoSQL databases.

Why Join Us?

- Join a dynamic, innovative group crafting the future of AI-powered creative tools.

- Work on impactful, large-scale projects that touch millions of users daily.

- Enjoy the benefits and resources of a leading global company with the agility of a startup environment.

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 or special need that requires accommodation to navigate our website or complete the application process, email [email protected].

AI Use Guidelines for Interviews:

Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.

At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it’s restricted during live interviews. See how we think about AI in the hiring experience.