Machine Learning Engineer

We are building foundational services and platforms to enable AI at scale within Adobe Experience Manager (AEM) and Content AI. Our focus is on applying machine learning techniques — from advanced retrieval-augmented generation (RAG) to personalization and customer behavior prediction — to power intelligent features that improve user experience and business outcomes.

We are looking for a hands-on Machine Learning Engineer who is eager to explore, evaluate, and "productionize" applied ML techniques. This role is ideal for someone with hands-on ML experience, eagerness to experiment with applied AI, and a good grasp of core software engineering principles.

You will partner with the business units to build and scale data products that address challenging business problems for Adobe’s enterprise customers in a direct co-innovation way. You will research, develop, and deploy large-scale machine learning solutions for business.

What You Will Do

• Explore and implement advanced RAG techniques and other applied ML methods to improve content relevance and answer quality.
• Contribute to experiments in customer behavior and preference prediction, evaluating different approaches.
• Build and maintain data pipelines to preprocess, enrich, and serve data for ML-driven features.
• Fine-tune and integrate existing ML models into production systems (rather than building models from scratch).
• Work with engineers and product managers to design ML-driven solutions aligned with product needs.
• Contribute to monitoring, evaluation, and iteration on deployed ML features.

What You Need To Succeed

• B.S. or M.S. in Computer Science, Engineering, Applied Mathematics, or related field, or equivalent practical experience.
• Proficiency in Python and common ML/DS libraries.
• Experience with applied ML techniques such as information retrieval, embeddings, recommendation systems, or NLP.
• Experience working with both structured and unstructured data (documents, text, logs, etc.).
• Basic understanding of software engineering practices (e.g., testing, version control, CI/CD, containerization).

Good to have aptitudes

• MLOps exposure (model deployment, monitoring, experiment tracking).
• Experience with vector databases, search engines, or embedding-based retrieval.
• Familiarity with distributed compute frameworks (Spark, Ray).
• Knowledge of personalization, recommendation systems, or customer behavior modeling.
• Exposure to REST APIs, Docker, Kubernetes.

What We Offer

• Opportunity to work on applied AI scenarios that directly impact enterprise-scale products.
• A collaborative environment focused on experimentation and innovation in search, personalization, and AI-driven user experiences.
• Growth opportunities into advanced ML engineering and MLOps practices as our AI initiatives expand.

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 applicable characteristics protected by law. Learn more.

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