EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting‑edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential. We are building production‑ready ML solutions and need a Lead Machine Learning Engineer to own end‑to‑end model delivery and MLOps rigor. You will create forecasting, recommendation, and optimization models, operationalize them with APIs and pipelines, and drive monitoring and continuous improvement—apply now. Responsibilities Design and build machine learning models for forecasting, classification, recommendation, segmentation and optimization Package models for production use and deliver them through APIs or scheduled jobs Implement monitoring, retraining and lifecycle management for ML solutions Apply MLOps best practices, including model versioning, experiment tracking and reproducible pipelines Track model behavior in production and recommend data‑driven improvements Contribute to technical design reviews and present well‑reasoned options with trade‑offs Document architecture decisions and enable knowledge transfer to internal teams Promote engineering standards, tools and best practices across the team Collaborate with business stakeholders to translate problems into machine learning solutions Requirements Proven hands‑on experience in ML Engineering or Data Engineering for production systems (5+ years) Demonstrated track record of shipping ML models used by real users, including at least 2 live production projects High proficiency in Python, PySpark and SQL Practical skills with Scikit‑learn, Databricks (production usage) and Delta Lake Strong expertise with REST APIs, Git, CI/CD pipelines, Docker and Jenkins Working knowledge of MLflow for model versioning and experiment tracking Solid background in time series forecasting, similarity techniques and computer vision models Deep understanding of feature engineering, model evaluation and monitoring Excellent communication skills to partner effectively with non‑technical stakeholders Sound judgment to balance model simplicity versus complexity appropriately English proficiency at B2 (Upper‑Intermediate) level or higher Nice to have Experience across retail, fashion, consumer goods or distribution domains Familiarity with enterprise planning tools such as SAP IBP, SAP M3 or SAC Exposure to building model monitoring dashboards using Power BI, Tableau or Looker Knowledge of semantic similarity or embeddings in product catalogs Understanding of multi‑country or multi‑currency platform challenges Ability to design Lakehouse architectures, including Medallion or Data Mesh We offer International projects with top brands Work with global teams of highly skilled, diverse peers Employee financial programs Paid time off and sick leave Upskilling, reskilling and certification courses Unlimited access to the LinkedIn Learning library and 22,000+ courses Global career opportunities Volunteer and community involvement opportunities EPAM Employee Groups Award‑winning culture recognized by Glassdoor, Newsweek and LinkedIn #J-18808-Ljbffr