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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 growth-through-acquisition to an outcome-driven, AI-native organization. As the Engineering Manager for Machine Learning & Data Science, you will lead a talented team of Data Scientists and ML Engineers solving complex operational challenges in logistics.
You will guide the strategic direction of applied AI initiatives while partnering closely with a Staff ML Engineer who owns core technical architecture. Your focus is on creating an inspiring, high-trust environment where top-tier engineers are empowered to build transformative AI products. You will champion a culture balancing rigorous engineering standards with rapid delivery of business value, fundamentally driven by measurable business outcomes rather than just delivery metrics.
Key responsibilities include: managing and coaching a high-performing team of Data Scientists and ML Engineers; fostering an inclusive, motivating workplace with psychological safety for innovation; championing AI adoption across the organization and exploring how foundational models and agents can enhance internal workflows; maintaining deep technical connection to your team's work, diving into codebases during ramp-up and occasionally contributing to tooling; driving agile execution and operational excellence, guiding the transition of R&D prototypes into robust, scalable production-ready ML systems; partnering with Product Managers to prioritize the backlog with clear ROI focus; and collaborating extensively with the Data & AI Platform team on MLOps infrastructure.
Sennder operates in a fast-paced, hybrid environment with 1,100 colleagues from 74 nationalities across offices in Berlin, Amsterdam, Wroclaw, and Milan. The company offers vibrant workspaces with healthy snacks, focus zones, and social areas, plus a sennCare well-being program.
REQUIREMENTS:
- 3+ years of experience successfully managing and scaling an Engineering, Machine Learning, or Data Science team
- 7+ years of prior experience as a Senior or Staff Individual Contributor with deep, hands-on experience deploying applied Machine Learning models into production environments
- Direct, hands-on experience building, deploying, and maintaining recommender systems, pricing algorithms, or complex statistical models in production
- High technical fluency with strong proficiency in Python, SQL, and Git
- Deep familiarity with modern ML and data stacks (Snowflake, AWS, Datadog)
- Experience with Jupyter Notebooks, workflow orchestration (Airflow or Flyte), frameworks like TensorFlow or PyTorch, and LLM tooling (LangChain)
- High emotional intelligence with strong track record of mentoring senior talent and leading teams through complex, ambiguous technical landscapes
- Sharp sense for commercial value, ability to cut through noise, and strong communication skills for managing expectations with executives and non-technical leaders
- PhD in Mathematical, Statistical, Computer Science, or related quantitative field is a strong plus
