ResponsibilitiesYou design, develop, and deploy robust machine learning models that address the unique challenges of power generation.These models are used to predict equipment failures, optimize maintenance schedules, enhance energy output, and more.You champion MLOps best practices to ensure the long-term sustainability and maintainability of data products.You implement robust monitoring, testing, and deployment pipelines.You work closely with domain experts, engineers, and operators to understand their needs, gather feedback, and deliver solutions that make a meaningful impact on their day-to-day work.You collaborate closely with the IT NEO Data Platform team, leveraging their shared Python packages and workflows to standardize the building and running of ML use cases.You stay abreast of the latest advancements in machine learning and explore emerging technologies, such as multi-agent reinforcement learning, to identify new opportunities for optimization.Required SkillsYou have a natural understanding and strong interest in the energy domain, with a desire to delve into the complexities of electricity production and its unique challenges.You bring over 4 years of proven experience in industrializing machine learning products, from concept to production.You are fluent in English and Dutch/French, allowing for effective collaboration and communication in multilingual environments.You are proficient with AWS cloud services, including S3, Glue, Athena, and Sagemaker.You have demonstrated expertise in Python development, specifically for data science and machine learning.You possess broad knowledge of machine learning frameworks, such as Scikit-learn, XGBoost, PyOD, and Darts, enabling effective implementation of diverse ML solutions.You have strong DevOps experience, including Git, CI/CD pipelines, and Docker containers, ensuring smooth deployment and maintenance of data-driven solutions.Having experience building multi-agent Retrieval Augmented Generation (RAG) systems is a plus.Bringing demonstrated experience working in industrial environments, preferably within the utility sector is a benefit.Possessing expertise in time series anomaly detection techniques is a valued addition.Experience working with historians, such as Aveva OSIsoft PI is an asset.Preferred SkillsExperience working with historians, such as Aveva OSIsoft PI is an asset.Seniority levelNot ApplicableEmployment typeFull-timeJob functionIndustries: IT Services and IT Consulting
#J-18808-Ljbffr