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sennder is Europe's leading digital freight forwarder, redefining road logistics through a unified platform powered by AI. The company is transitioning from acquisition-driven growth to an outcome-driven, AI-native organization. As a Machine Learning Engineer, you will join a highly talented ML team working on applied, research-oriented machine learning projects with direct business impact.
You will own end-to-end ML projects spanning from R&D prototyping through production deployment. Your work will focus on several high-impact areas: optimizing the dynamic pricing engine through bid estimation and margin-optimization algorithms; building predictive models for carrier behavior and market capacity forecasting; maintaining and improving recommender systems; exploring new ML applications in logistics (routing, network optimization); and integrating LLMs and AI agents into internal products and workflows.
The role demands a balanced skill set: approximately 70% deep data science and statistical exploration, paired with 30% ML engineering fundamentals. You will work directly with end-users, operators, and Product Managers to understand workflows and drive product direction. You'll partner closely with the Data & AI Platform team to deploy models via internal MLOps infrastructure, providing feedback to shape engineering standards.
Required qualifications include 5+ years of hands-on experience in Data Science or Machine Learning Engineering. You must have strong statistical foundations (hypothesis testing, data exploration), production ML deployment experience, and proficiency in Python, SQL, and Git. Experience with cloud data warehouses (Snowflake), Jupyter Notebooks, and visualization tools (Streamlit, PowerBI) is essential. You should understand how to set up, evaluate, and leverage LLMs in production. Strong business acumen to translate logistics problems into data-driven solutions and excellent collaboration skills are critical.
The role can be based in Barcelona, Berlin, or Amsterdam offices. sennder offers a vibrant, hybrid work environment with 1,100 colleagues from 74 nationalities, well-being initiatives, and growth opportunities in a fast-paced, outcome-focused culture.
