Machine Learning Engineer - 4

Machine Learning Engineer - 4 At Adobe, we are redefining how businesses deliver personalized digital experiences at scale. The Adobe Target Personalization team drives this transformation by applying sophisticated machine learning techniques. We use large-scale data processing and real-time decisioning. These efforts power intelligent recommendations and personalized customer experiences. We are looking for a senior Machine Learning Engineer who is passionate about building scalable ML systems and driving innovation in user-specific content delivery and suggestion technologies. This role combines strong backend engineering with deep ML expertise to deliver impactful, production-grade solutions for personalized experience. What You’ll Do Lead the design and development of advanced machine learning models for personalization and recommendation systems (e.g., ranking, retrieval, collaborative filtering, deep learning-based recommenders). Own the end-to-end ML lifecycle —from problem formulation and data exploration to model development, deployment, monitoring, and continuous improvement. Build scalable, low-latency systems that power real-time personalization for millions of users. Drive ML-Ops excellence by implementing standard processes in model versioning, CI/CD pipelines, monitoring, and automated retraining. Collaborate multi-functionally with product managers, data scientists, and platform engineers to translate business goals into impactful ML solutions. Architect robust data pipelines using distributed systems (e.g., Spark, Hadoop) to process large-scale datasets efficiently. Stay ahead of industry trends in AI/ML (including GenAI and AI agents) and bring innovative ideas into production. What You’ll Need to Succeed Must-Have Qualifications 7 years of experience in Machine Learning Engineering and backend development . Strong experience building and deploying recommendation systems or personalization models at scale. Solid understanding of ML algorithms such as collaborative filtering, ranking models, embeddings, deep learning, and reinforcement learning. Hands-on experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong backend engineering skills in Java / Python / Scala , with experience building production-grade services. Experience with large-scale data technologies such as Apache Spark, Hadoop, and distributed computing frameworks. Experience with ML-Ops practices , including model deployment, monitoring, and lifecycle management. Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. Good-to-Have Experience with real-time decisioning systems or low-latency inference pipelines. Exposure to Generative AI, LLMs, or AI agents applied to personalization use cases. Knowledge of MapReduce paradigms and large-scale data processing optimization. Experience working with A/B testing frameworks and experimentation platforms. Why Join Us Work on industry-leading personalization products used by top global brands. Solve complex, high-scale problems impacting millions of users in real time. Be part of a high-impact, forward-thinking team crafting the future of AI-powered experiences. Collaborate with individuals who consistently apply innovative thinking in ML, data, and distributed systems. 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 employe ... (truncated, view full listing at source)