Senior ML Engineer IRC280775

Senior ML Engineer IRC – GlobalLogic Join our engineering team at GlobalLogic as a Senior Machine Learning Engineer. You will help evolve Batch AI, an AI‑powered system that optimizes material feeding in concrete production to enable more accurate, consistent, and autonomous batching operations. Overview Your work will involve designing, training, and evaluating production‑grade machine learning models that directly impact industrial performance. You will collaborate closely with engineers and the Product Operations team, taking ownership of end‑to‑end model development. Qualifications (Must‑Have) BSc or MSc in Data Science, Applied Mathematics, Computer Science, or equivalent practical experience 5+ years of hands‑on experience in applied machine learning, focusing on regression, forecasting, or optimization Proven experience building production‑grade ML pipelines from experimentation to deployment Strong grasp of data‑science concepts such as cross‑validation, quantile modeling, and model safeguard techniques Strong background in Python and data‑science libraries, writing clean, efficient, production‑ready codeExperience using modern development tools and practices: Git, code reviews, automated testing, CI/CD pipelines Solid understanding of data lifecycle management, time‑series feature engineering, and retraining strategies Experience with ML model monitoring, versioning, and continuous retraining frameworks Familiarity with cloud ML ecosystems (Azure or AWS) Comfortable documenting and presenting analytical findings to mixed technical and non‑technical audiences Effective communication and collaboration skills; self‑driven, organized, capable of delivering with minimal supervision Nice‑to‑Have Experience with Azure ML, CosmosDB, Service Bus, and Kubernetes Experience with AWS SageMaker, ECS Fargate, SQS/EventBridge, and DocumentDB Exposure to industrial data from manufacturing equipment, batching systems, or other IoT‑connected process control environments such as manufacturing, logistics, or energy sectors Experience applying software development and engineering best practices, including architectural, design, and coding principles Experience with containerized workloads (Docker) Responsibilities Design, train, and validate machine learning models that improve process performance and stability in concrete batching operations Lead end‑to‑end model development, from data exploration and feature engineering to deployment and validation Define and implement retraining and validation strategies that ensure continuous performance improvement Work closely with engineers to ensure models integrate efficiently with production systems in Azure and AWS environments Propose data selection and quality control methods to improve training representativity Contribute to monitoring and evaluation approach for ongoing model health Document methodologies, experiments, assumptions, and decisions to maintain clarity and reproducibility Collaborate with team members, the Product Operations team, and other stakeholders to support large‑scale deployment What We Offer Culture of Caring. We prioritize an inclusive culture where people come first and you can build meaningful connections with supportive teammates and leaders. Learning and Development. You’ll have continuous learning opportunities through programs, training curricula, and hands‑on projects that help you grow personally and professionally. Interesting & Meaningful Work. You’ll work on impactful projects that reshape industries and bring new solutions to market. Balance and Flexibility. Multiple career areas and work arrangements let you find a balance between your work and life. High‑Trust Organization. Integrity and trust are core to our values; we promote transparency and ethical conduct across the business. About GlobalLogic GlobalLogic, a Hitachi Group company, is a trusted digital engineering partner to the world’s largest and most forward‑thinking companies. Since 2000, we’ve been at the frontier of the digital revolution, helping clients transform businesses, redefine industries, and create innovative digital products, platforms, and services. #J-18808-Ljbffr