Machine Learning Engineer

About this role

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Skills you'll use

What you'll do

• 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.

Who can apply

• - 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.

Perks & benefits

About Adobe

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