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sennder HQ Berlin
Live, first seen by us 56 days agoEmployment type in the employer’s posting: FULL_TIMEFrom the employer’s posting
As the Engineering Manager for our Machine Learning & Data Science team, you will lead a highly talented group of Data Scientists and ML Engineers tackling some of the most complex operational challenges in logistics.
Rather than just focusing on the "how" and the metrics of delivery (such as velocity, predictability, and engineering quality), you will be fundamentally driven by the "why"—ensuring your team’s output consistently translates into measurable business outcomes that drive real margin and efficiency gains for the company.
Manage, coach and grow a team of data scientists and ML engineers
Guide the move of R&D prototypes into production-ready ML systems
Prioritize the backlog with Product Managers around measurable ROI
Drive AI adoption within the department and beyond
Align with the Data & AI Platform team on global MLOps infrastructure
As the Engineering Manager for our Machine Learning & Data Science team, you will lead a highly talented group of Data Scientists and ML Engineers tackling some of the most complex operational challenges in logistics. This is a dynamic, high-impact role where you will guide the strategic direction of our applied AI initiatives, while partnering closely with our Staff ML Engineer who owns the core technical architecture and technical leadership. You will champion a culture of excellence that balances rigorous engineering standards with the rapid delivery of business value.
Rather than just focusing on the "how" and the metrics of delivery (such as velocity, predictability, and engineering quality), you will be fundamentally driven by the "why"—ensuring your team’s output consistently translates into measurable business outcomes that drive real margin and efficiency gains for the company. You will partner tightly with our AI Lead Product Managers to shape a high-ROI roadmap and collaborate closely with our Data & AI Platform (MLOps) team to ensure seamless deployment. Ultimately, your job is to create an inspiring, high-trust environment where top-tier engineers are empowered to build transformative AI products.
Manage, coach, and support a high-performing team of Data Scientists and ML Engineers
Guide the team in transitioning R&D prototypes into robust, scalable, production-ready ML systems
Partner tightly with Product Managers to ruthlessly prioritize the backlog
You will drive AI adoption within the department and beyond
collaborate extensively with the Data & AI Platform team to align on global MLOps infrastructure
Leadership Experience: 3+ years of experience successfully managing and scaling an Engineering, Machine Learning, or Data Science team.
Technical Depth: You remain highly technically fluent. You possess strong proficiency in Python, SQL, and Git, and are deeply familiar with modern ML and data stacks (Snowflake, AWS, Datadog...). Experience utilizing Jupyter Notebooks for exploration, workflow orchestration (Airflow or Flyte), frameworks like TensorFlow (or PyTorch), and LLM tooling (LangChain) is required to effectively review code and deeply understand your team's day-to-day challenges.
- Technical Depth: You remain highly technically fluent. You possess strong proficiency in Python, SQL, and Git, and are deeply familiar with modern ML and data stacks (Snowflake, AWS, Datadog...). Experience utilizing Jupyter Notebooks for exploration, workflow orchestration (Airflow or Flyte), frameworks like TensorFlow (or PyTorch), and LLM tooling (LangChain) is required to effectively review code and deeply understand your team's day-to-day challenges. - Academic Background: A PhD in a Mathematical, Statistical, Computer Science, or related quantitative field is a strong plus. - Management Craft: High emotional intelligence with a strong track record of mentoring senior talent, driving career growth, and leading teams through complex, ambiguous technical landscapes.
As Europe’s leading digital freight forwarder, we are building a smarter, faster, and more sustainable future for freight, powered by a single, unified platform that already runs our entire business.
In the employer’s words · Read in context
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Day 56
Up longer than most. Similar jobs usually come down between day 7 and day 54.
From 8,098 similar postings that came down. Coming down is not always a hire.
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- Domain ML Experience: Direct, hands-on experience building, deploying, and maintaining recommender systems, pricing algorithms, or complex statistical models in a production setting. - Technical Depth: You remain highly technically fluent. You possess strong proficiency in Python, SQL, and Git, and are deeply familiar with modern ML and data stacks (Snowflake, AWS, Datadog...). Experience utilizing Jupyter Notebooks for exploration, workflow orchestration (Airflow or Flyte), frameworks like TensorFlow (or PyTorch), and LLM tooling (LangChain) is required to effectively review code and deeply understand your team's day-to-day challenges. - Academic Background: A PhD in a Mathematical, Statistical, Computer Science, or related quantitative field is a strong plus.
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New Data Leadership postings at the employers we follow are up 7% over the last 5 weeks compared with the 5 before.
Each bar is one week of new postings. The darkest bars are the last 5 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
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sennder HQ Berlin
- Vibrant Workspaces: Our offices are equipped with healthy snacks, focus zones, and social areas to keep you energized and connected. Highlights include a slide in our Wroclaw office and a sunny rooftop terrace in Berlin, Amsterdam, and Milan. - Culture: Work in a fast-paced, hybrid environment with 1,100 talented, diverse colleagues from 74 nationalities. We prioritize well-being through initiatives like our sennCare program and a partnership with nilo. - Growth & Rewards: We believe in rewarding our team for their commitment and contributions to our long-term success. Our compensation package may include performance bonuses, referral rewards, or equity that align with our goal of building a thriving company together.
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