.sennder is Europe's leading digital freight forwarder. In a traditional industry, we are moving fast to digitize and automate all road logistics processes. We move trucks with courage and the power of data to unlock endless and sustainable capacity at exceptional quality. Get to know us better by reviewing our " About Us " presentation.We are looking for a Senior Machine Learning Engineer (MLOps) to join our central ML Recommendations team as part of sennAI department. The department's mission is to achieve "Automated & Data-Driven Road Logistics". We're a large, diverse and multidiscplinary group of ML& AI engineers, data scientists, backend/frontend engineers and technical product people that are passionate by the new AI-empowered digitalization wave that is changing our world. We want to attract and train world-class talent to form a incredible group that can provide you the most productive and growth-friendly time of your career.Design and maintain scalable ETL and MLOps infrastructureDefine the new state-of-the-art for machine learning engineering in the road logistics services; Design and develop health and performance monitoring tools (MLOps) of data pipelines and the machine learning services in production; Design and improve heterogeneous, asynchronous and high-performance large-data processing pipelines from/to multiple sources/destinations; Operationalize innovative, data-intensive, end-to-end machine-learning(ML)-based decision enginesCollaborate with cross-functional teams to understand business requirements, translate them into technical specifications, and deliver robust ML solutions that address real-world logistics challengesMentor junior team members, sharing your expertise and best practices in ML engineering, MLOps, and software development to foster a culture of learning and innovation within the teamHas extensive experience with one or more orchestration tools (e.G Airflow, Flyte, Kubeflow)Has experience working with MLOps tools like experiment tracking, model registry tools and feature stores (e.G MLFlow, Sagemaker, Azure MLOps, Feast, Databricks)Has extensive experience with DevOps focused around data intensive applications. You are comfortable with infrastructure-as-code, you have used the likes of Terraform and Kubernetes extensively; Has experience building and scaling model serving tools, i.E building APIs with tight SLAs; Highly motivated with excellent communication and strong interpersonal skillsSolid Python software engineering skills, including best practices like CI/CD and GitExperience in designing/implementing virtualization services (e.G
