Machine Learning Engineer

Role overview Build and improve reinforcement learning systems for production scheduling, including the simulated factory environments used to train and evaluate them. The work combines applied machine learning, manufacturing knowledge, production-quality Python development, and collaboration with engineers and customers to turn operational needs into working features.

Responsibilities - Develop, test, and maintain reinforcement learning agents and their training and evaluation scripts. - Design and optimize Digital Twin simulation features using Python, NumPy, and Pandas. - Write scalable Python code, unit and integration tests, and participate in code reviews. - Improve agent algorithms, reward functions, and architecture. - Configure and maintain Python environments, and collaborate through Git-based workflows. - Discuss customer requirements and translate them into technical work.

Requirements - Degree or equivalent background in computer engineering, mathematics, machine learning, industrial engineering, or a related field. - At least five years of Python experience. - At least two years working in factory shopfloor operations as an engineer or planner, or with factory ERP/MES systems. - Knowledge of manufacturing processes, including discrete manufacturing, line production, and engineer-to-order. - Basic reinforcement learning knowledge and experience developing or applying RL algorithms.

Benefits and work setup - Full-time role with remote work or a hybrid arrangement from a Berlin coworking space. - Flexible working hours and a company-provided laptop. - Small-team ownership, collaboration, and a flat hierarchy.