Experteer Overview
As a Machine Learning Engineer at sennder you will own end-to-end ML from Ru0026amp;D to production, applying data science to drive pricing, forecasting, and recommender systems. You will work closely with end-users, product managers, and platform engineers to translate operational pain points into measurable ML outcomes. The role blends deep data exploration with practical ML engineering to deploy scalable models that improve margin, cost, and service. This position offers impact across Europe’s leading digital freight platform and invites you to shape AI-powered logistics initiatives.

Compensaciones / Ventajas
• Pricing engine optimization: develop bid estimation and margin models to boost profitability
• Carrier forecasting: build predictive models for carrier behavior and capacity
• Recommender systems: maintain and enhance models to improve day-to-day operations
• Explore new ML applications in logistics (routing, network optimization) and turn them into scalable solutions
• Product discovery with PMs to translate pain points into ML hypotheses and rapid prototypes
• AI u0026 LLM integration: evaluate trade-offs between LLMs, traditional models, or heuristics and build internal products
• End-to-end deployment:



manage full lifecycle from Ru0026D to production release and monitoring
• Platform collaboration: work with Data u0026 AI Platform to deploy models on internal infrastructure

Responsabilidades
• 5+ years of hands-on Data Science or ML Engineering experience
• Strong foundation in statistical analysis and data exploration; working knowledge of regression and classification
• Experience deploying models to production; modular code and software engineering practices
• Proficiency in Python, SQL, and Git; experience with cloud data warehouses (e.g., Snowflake)
• Jupyter Notebooks for data exploration; building data apps/dashboards (Streamlit, PowerBI)
• Understanding of LLMs and AI tools in production
• Business acumen to translate complex logistics problems into data-driven solutions
• Strong collaboration and communication with PMs, end-users, and cross-functional teams

Requisitos principales
• hybrid work environment
• well-being initiatives (sennCare)
• office amenities and social areas
• growth and rewards including performance bonuses or equity
• diversity and inclusive culture
• global team with 74 nationalities

📌 Machine Learning Engineer (Barcelona)
🏢 Sennder
📍 Barcelona