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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. This Machine Learning Engineer role joins a highly talented ML team to turn sennder's data and operational advantages into competitive edges in margin, cost, and service.
The position is applied machine learning focused on innovative, research-oriented projects across a diverse portfolio of high-impact initiatives. You will work on optimizing the Recommendation and Pricing engines while building greenfield solutions. The role demands approximately 70% deep Data Science and statistical exploration paired with 30% Machine Learning Engineering skills to transition prototypes into production systems.
Key responsibilities include: developing and iterating on bid estimation algorithms and margin-optimization models for the dynamic pricing engine; building predictive models to forecast carrier behavior and market capacity; maintaining and improving recommender systems; exploring new ML applications for logistics challenges like freight routing and network optimization; partnering with Product Managers on product discovery and translating operational pain points into ML hypotheses; leveraging foundational models and AI agents as both engineering accelerators and core product components; collaborating with the Data & AI Platform team on model deployment; and maintaining end-to-end ownership from R&D through production release and monitoring.
You will work directly with end-users, operators, and Product Managers to understand workflows and influence product direction. The role emphasizes pragmatic evaluation of trade-offs—choosing the right solution whether that's an LLM, traditional ML model, or simple heuristic.
Required qualifications: 5+ years hands-on experience in Data Science or Machine Learning Engineering; strong foundation in statistical analysis, hypothesis testing, and data exploration; experience deploying models to production with modular code and software engineering best practices; strong Python, SQL, and Git proficiency; experience with cloud data warehouses (Snowflake), Jupyter Notebooks, and interactive dashboards (Streamlit, PowerBI); solid understanding of LLM setup, evaluation, and production deployment; ability to translate complex logistical problems into data-driven solutions; strong communication skills for cross-functional collaboration.
The company offers vibrant workspaces with healthy snacks and social areas across Berlin, Amsterdam, and other offices; a fast-paced hybrid environment with 1,100 colleagues from 74 nationalities; well-being initiatives including the sennCare program; and growth and rewards aligned with commitment and contributions.
