Senior ML Engineer IRC280775

hace 4 semanas


Buenos Aires, Argentina GlobalLogic A tiempo completo

AI, Cloud ML, cloud data pipelines, Data Science, Machine Learning, Python About the Role: You will be part of Command Alkon’s Engineering team, driving the evolution of Batch AI, our AI-powered system that optimizes material feeding in concrete production. Batch AI combines sensor data with predictive and machine learning models to make batching operations more accurate, consistent, and autonomous. As a Senior ML Engineer, you will apply machine learning engineering and applied data science techniques to design, train, and evaluate models that directly impact industrial performance, working closely with engineers and the Product Operations team. This is a hands‑on role for someone who thrives on ownership, experimentation, and delivering real‑world impact. You will play a key role in advancing the intelligence and reliability of industrial processes powered by Batch AI. Requirements 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, with a focus on regression, forecasting, or optimization. Proven experience in 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, with the ability to write clean, efficient, and production‑ready code. Experience using modern development tools and practices, including Git and related workflows, code review processes, automated testing, and CI/CD pipelines. Solid understanding of data lifecycle management, including 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, and able to deliver 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). Job 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 the 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 as needed to support large‑scale deployment. What we offer Culture of caring. At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every level, we consistently put people first. From day one, you’ll experience an inclusive culture of acceptance and belonging, where you’ll have the chance to build meaningful connections with collaborative teammates, supportive managers, and compassionate leaders. Learning and development. We are committed to your continuous learning and development. You’ll learn and grow daily in an environment with many opportunities to try new things, sharpen your skills, and advance your career at GlobalLogic. With our Career Navigator tool as just one example, GlobalLogic offers a rich array of programs, training curricula, and hands‑on opportunities to grow personally and professionally. Interesting & meaningful work. GlobalLogic is known for engineering impact for and with clients around the world. As part of our team, you’ll have the chance to work on projects that matter. Each is a unique opportunity to engage your curiosity and creative problem‑solving skills as you help clients reimagine what’s possible and bring new solutions to market. In the process, you’ll have the privilege of working on some of the most cutting‑edge and impactful solutions shaping the world today. Balance and flexibility. We believe in the importance of balance and flexibility. With many functional career areas, roles, and work arrangements, you can explore ways of achieving the perfect balance between your work and life. Your life extends beyond the office, and we always do our best to help you integrate and balance the best of work and life, having fun along the way High‑trust organization. We are a high‑trust organization where integrity is key. By joining GlobalLogic, you’re placing your trust in a safe, reliable, and ethical global company. Integrity and trust are a cornerstone of our value proposition to our employees and clients. You will find truthfulness, candor, and integrity in everything we do. 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 forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services. #J-18808-Ljbffr



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