Senior Machine Learning Engineer

Senior Machine Learning Engineer Location: Berlin, Germany Work Arrangement: Hybrid – 3 days in the office, 2 days remote Industry: Technology | E-commerce | Logistics Salary: Not disclosed About the Role An opportunity is available for an experienced Senior Machine Learning Engineer to develop, deploy, and optimise large-scale machine learning systems within a global technology and delivery platform. The position focuses on building production-ready ML solutions that improve logistics operations, demand forecasting, delivery time predictions, pricing, and operational efficiency. Working within a collaborative Data Science and Engineering environment, this role involves developing scalable machine learning applications, real-time data pipelines, and cloud-based systems that support millions of daily transactions. Key Responsibilities - Design, develop, and deploy scalable machine learning models and applications. - Research and implement advanced ML techniques to solve complex logistics and forecasting challenges. - Develop predictive models for delivery time estimation, supply and demand forecasting, and pricing optimisation. - Build and maintain production-grade machine learning pipelines and infrastructure. - Develop high-performance Python applications and services. - Deploy and manage machine learning solutions using cloud platforms such as AWS or Google Cloud Platform. - Work with real-time data streaming technologies and event-driven architectures. - Develop and optimise microservices and cloud-native applications. - Implement tools, data pipelines, and evaluation frameworks to support ML experimentation and deployment. - Monitor and improve model performance, scalability, and reliability. - Collaborate with Data Scientists, Software Engineers, Product Managers, and other technical stakeholders. - Contribute to engineering best practices, technical design, and continuous improvement initiatives. Required Skills & Experience - Strong professional experience in Machine Learning Engineering, including developing and deploying production ML systems. - Advanced Python programming and software engineering skills. - Experience developing real-time data streaming solutions for forecasting, logistics, or similar applications. - Proven ability to design, deploy, and maintain scalable ML solutions in production environments. - Experience with AWS, Google Cloud Platform, or comparable cloud technologies. - Strong understanding of microservices, event-driven architecture, serverless computing, and cloud architecture patterns. - Experience deploying applications using Kubernetes. - Experience working with large-scale, real-time production systems handling millions of requests or transactions. - Strong problem-solving skills and the ability to work independently on complex technical challenges. - Experience collaborating with cross-functional engineering and product teams. Preferred Skills & Experience - Experience with Docker, Airflow, MLflow, or Apache Flink. - Knowledge of MLOps practices and automated machine learning deployment pipelines. - Experience with logistics optimisation, demand forecasting, or dynamic pricing. - Experience developing high-throughput, low-latency ML applications. - Background in e-commerce, online marketplaces, delivery platforms, or logistics technology. Working Arrangements This is a hybrid position based in Berlin, Germany, requiring: - 3 days per week working from the Berlin office. - 2 days per week working remotely. Additional Information This position is suited to experienced machine learning engineers with strong software engineering capabilities and a proven track record of deploying scalable, real-time ML systems. Hands-on experience with Python, cloud infrastructure, Kubernetes, and production machine learning applications is particularly important.