Machine Learning Engineer

Experteer Overview In this role you will join sennder’s ML team to translate data-driven insights into high-impact production models. You’ll work across pricing, forecasting, and recommender systems, while exploring new ML-driven solutions for logistics challenges. You will collaborate with product, end-users, and platform engineers to ship end-to-end models from research through production. Your work will help accelerate profitability, capacity planning, and operational efficiency in Europe’s leading digital freight platform. Pay / Benefits * Pricing engine optimization: develop bid estimation and margin models to drive profitability * Carrier forecasting: build predictive models for carrier behavior and market capacity * Recommender systems: maintain and improve systems supporting daily operations * Industry innovation & applied ML: explore ML solutions for routing and network optimization * Product discovery & ideation: translate operational pain points into ML hypotheses and prototypes * AI & LLM integration: use foundational models and AI tools to accelerate workflows and build internal products * Platform collaboration: work with Data & AI Platform (MLOps) to deploy models and influence standards * End-to-end execution: manage projects from R&D to production release and monitoring Tasks * 5+ years of hands-on experience in Data Science or ML Engineering * Strong foundation in statistical analysis, hypothesis testing, and data exploration * Working knowledge of ML approaches for regression and classification * Production-ready ML deployment experience * Proficiency in Python, SQL, and Git * Experience with cloud data warehouses (e.g., Snowflake) * Jupyter Notebooks for data exploration; creating interactive dashboards (e.g., Streamlit, PowerBI) * Knowledge of how to set up and evaluate LLMs in production * Business acumen to translate logistics problems into data-driven solutions * Strong collaboration and communication skills with cross-functional teams Key requirements * hybrid work environment * performance bonuses * referral rewards * equity * sennCare program * nilo partnership

Strong * AI & LLM integration: use foundational models and AI tools to accelerate workflows and build internal products * Platform collaboration: work with Data & AI Platform (MLOps) to deploy models and influence standards * End-to-end execution: manage projects from R&D to production release and monitoring Tasks * 5+ years of hands-on experience in Data Science or ML Engineering * Strong foundation in statistical analysis, hypothesis testing, and data exploration * Working knowledge of ML approaches for regression and classification * Production-ready ML deployment experience * Proficiency in Python, SQL, and Git * Experience with cloud data warehouses (e.g., Snowflake) * Jupyter Notebooks for data exploration; creating interactive dashboards (e.g., Streamlit, PowerBI) * Knowledge of how to set up and evaluate LLMs in production * Business acumen to translate logistics problems into data-driven solutions * Strong collaboration and communication skills with cross-functional teams Key requirements * hybrid work environment * performance bonuses * referral rewards * equity * sennCare program * nilo partnership