Senior Machine Learning Engineer job opportunity at Adobe.

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Adobe Senior Machine Learning Engineer
Experience: 6-years
Pattern: full-time
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loacation Noida, India
loacation Noida....India

Our Company Changing the world through digital experiences is what Adobe’s all about. We give everyone—from emerging artists to global brands—everything they need to design and deliver exceptional digital experiences! We’re passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen.  We’re on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours!   Adobe is seeking a Machine Learning Engineer to join the Genuine Engineering team—a group dedicated to protecting Adobe’s ecosystem from fraud, abuse, and misuse through intelligent, ML-driven systems. You’ll work on designing, building, and scaling machine learning models that detect fraudulent behavior, prevent account sharing, and ensure a safe and seamless experience for millions of Adobe users worldwide. In this role, you’ll collaborate closely with data scientists, product engineers, and infrastructure teams to take ML models from experimentation to full-scale deployment. You’ll combine deep technical expertise in ML, data engineering, and distributed systems with a passion for solving complex, high-impact problems. Key Responsibilities Lead the design, development, and deployment of production-grade ML models for fraud detection, anomaly detection, and behavioral analytics. Translate research and prototypes into scalable, reliable ML systems running across Adobe’s platforms. Collaborate cross-functionally with product, data, and infrastructure teams to define technical requirements and deliver high-impact solutions. Build and optimize data pipelines for feature engineering, model training, and real-time inference using modern tools (Databricks, Spark, etc.). Ensure model scalability, reliability, and performance through continuous monitoring, evaluation, and iteration. Contribute to MLOps practices including CI/CD, model versioning, and automated retraining workflows. Stay ahead of advancements in ML/AI , bringing new techniques and innovations to Adobe’s products. Minimum Qualifications Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or related field. 6+ years of professional experience building and deploying ML solutions at scale. Strong programming expertise in Python , with hands-on experience in PyTorch, TensorFlow , or similar frameworks. Proven experience with distributed data systems (Spark, Databricks, or Hadoop ecosystem). Deep understanding of the end-to-end ML lifecycle —from data collection to deployment and monitoring. Strong grasp of model optimization , inference efficiency, and production system integration. Experience working in cloud environments (AWS, Azure, or GCP) with containerized workflows (Docker, Kubernetes). Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment. Preferred Qualifications Experience in fraud detection, anomaly detection, or behavioral modeling . Familiarity with responsible AI frameworks focusing on fairness, interpretability, and transparency. Contributions to open-source ML frameworks or publications in applied ML. 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. Adobe aims to make Adobe.com 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  accommodations@adobe.com  or call (408) 536-3015.

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