AI-Driven ML Engineer for Dynamic Pricing & Logistics

senndertechnologies-gmbh; Barcelona; Híbrido; EUR 90.000 - 120.000; Jornada completa

Descripción de la vacante

sennder is seeking a skilled Machine Learning Engineer to join our Barcelona-based team. You will lead data-driven projects spanning predictive modeling, recommender systems, and pricing optimization, working closely with Product Managers and end-users to translate complex logistics challenges into practical ML solutions.

Ideal candidates have 5+ years in data science or ML engineering, strong statistical background, and experience deploying models to production.

Formación

• 5+ years of hands-on experience in Data Science or Machine Learning Engineering.
• Strong foundation in statistical analysis, hypothesis testing, and deep data exploration.
• Experience deploying models to production environments and writing modular code.
• Proficiency in Python, SQL, and Git; familiarity with cloud data warehouses and data visualization tools.
• Understanding of LLMs and AI tools in production settings.
• Ability to translate complex logistics problems into data-driven solutions.
• Excellent collaboration with Product Managers, end-users, and cross-functional teams.

Responsabilidades

• Develop and iterate on predictive models for carrier behavior and market capacity.
• Improve and maintain recommender systems and pricing engines.
• Collaborate with ML Platform team to deploy models in production.
• Engage with end-users and Product Managers to align ML work with business outcomes.
• Explore new ML approaches for logistics challenges and scalable solutions.

Conocimientos

Python

SQL

Git

Snowflake

Jupyter Notebooks

Streamlit

PowerBI

LLMs

Data-driven decision making

Collaboration

Herramientas

Snowflake

Jupyter Notebooks

Streamlit

PowerBI

Descripción del empleo

sennder is seeking a skilled Machine Learning Engineer to join our Barcelona-based team. You will lead data-driven projects spanning predictive modeling, recommender systems, and pricing optimization, working closely with Product Managers and end-users to translate complex logistics challenges into practical ML solutions.

Ideal candidates have 5+ years in data science or ML engineering, strong statistical background, and experience deploying models to production.