5 Machine Learning Engineer Jobs Berlin

Design, develop, and maintain features using Machine Learning Models, NLP, Information Retrieval and other relevant methodologies., Deliver key data and insights into leading software platforms used by large enterprises via API., Source, process, and standardize data from multiple sources, ensuring data quality., Train, optimize, and evaluate various models to enhance accuracy and effectiveness., Deploy and maintain models on AWS, particularly with SageMaker, while managing production pipelines., Develop and explore innovative methods for modeling multilingual, semi-structured, and hierarchical data.

Explore the latest literature on state-of-the-art machine learning concepts related to time-series prediction, digital twin modeling, and energy optimization algorithms., Collaborate with our ML team to develop prototypes for forecasting heating demand and PV production using state-of-the-art ML models, and evaluate different approaches., Assist in creating state-of-the-art data-driven models for heating systems., Support the training of RL agents to optimize the operational control of heat pumps for optimal efficiency., Contribute to the design and implementation of innovative algorithms that improve energy management and efficiency., Work closely with energy engineers, ML engineers, and data scientists to develop innovative features for our smart home energy management system., Effectively present findings and insights in a concise and understandable manner, ensuring clarity for all stakeholders.

Design, train, evaluate, and deploy deep learning models in speech recognition and NLP, Engineer large self-supervised trainings, Implement fast inference for mobile devices and hosted environments, Communicate with customers to gather feedback and understand their challenges, Translate user insights into product decisions

Unterstützung des Teams bei der Entwicklung und Implementierung innovativer ML-basierter Lösungen, Einbindung in die Entwicklung und Umsetzung von Machine Learning Use Cases und Prototypen in einem agilen, iterativen Umfeld, Eigenständige (Themen-)Recherchen zur proaktiven Projektbearbeitung, Weiterentwicklung technischer Fähigkeiten und Beteiligung am technischen Kompetenzaufbau innerhalb der Science Group

Technische Orientierung für ein kleines Team von Softwareentwicklern bieten, Verantwortung für die Planung und Durchführung spannender Projekte übernehmen, Gestaltung der technischen Architektur der Projekte, Optimierung der AWS-Infrastruktur und effizientes Cloud-Management, Datengetriebene Ansätze vorantreiben und KI-Lösungen entwickeln