Lead and develop a team of Data Scientists and ML Engineers building production machine-learning systems for logistics. Drive AI adoption, roadmap prioritization, agile execution, and measurable business outcomes. Partner with Product Managers, Staff ML Engineers, and the MLOps platform team to deploy scalable solutions. The role requires deep hands-on experience with production ML, recommender systems, pricing algorithms, statistical models, and modern data and AI technologies, alongside strong people leadership and executive communication skills.
About sennder
Sennder is redefining road logistics. 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. We are moving from a decade of growth through acquisition to a company that is outcome-driven, outward-focused, and AI-native by design.
Logistics is one of the best possible use cases for AI, and unlike most of our peers, we own the full loop: the platform, the operations, and the data connecting them. That closed feedback loop is a compounding advantage most competitors can’t replicate. This role exists to turn that advantage into sennder’s sharpest edge in margin, cost, and service, because AI will give us that edge if we lead, or become a risk if we lag.
Role Overview
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.
Key Responsibilities
- People Leadership & Culture: Manage, coach, and support a high-performing team of Data Scientists and ML Engineers. Foster a highly motivating, inclusive team spirit, creating an inspiring workplace where engineers feel empowered, challenged, and psychologically safe to innovate.
- AI Adoption & Transformation: Champion our journey toward becoming a fully AI-native business. You will drive AI adoption within the department and beyond, continuously exploring how foundational models and agents can be leveraged to bring our internal workflows and internal products to the next level.
- Technical Enablement: Maintain a deep connection to the technical reality of your team. While your primary focus is on people and roadmap execution, you will dive into the codebase during your ramp-up and occasionally contribute to tooling or non-critical path initiatives. You will use this context to seamlessly unblock your engineers and support the Staff Engineer's architectural vision.
- Delivery & Execution: Drive agile execution and operational excellence. Guide the team in transitioning R&D prototypes into robust, scalable, production-ready ML systems, maintaining a high bar for engineering quality and predictability.
- Roadmap & Business Value: Partner tightly with Product Managers to ruthlessly prioritize the backlog. Focus the team on initiatives with clear, measurable ROI, perfectly aligning technical possibilities with sennder's strategic commercial goals.
- Cross-Functional Collaboration: Partner with your Staff ML Engineer to navigate deep technical challenges, and collaborate extensively with the Data & AI Platform team to align on global MLOps infrastructure, ensuring we build scalable and maintainable solutions.
Qualifications
- Leadership Experience: 3+ years of experience successfully managing and scaling an Engineering, Machine Learning, or Data Science team.
- Technical Foundation: 7+ years of prior experience working as a Senior or Staff Individual Contributor, with deep, hands-on experience deploying applied Machine Learning models into production environments.
- 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.
- 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.
- Business Acumen: You live by "Outcome over Output." You have a sharp sense for commercial value, an ability to cut through noise, and the communication skills to expertly manage expectations with executive stakeholders and non-technical business leaders.
What we offer
- Impact: Build the data and AI foundation for Europe’s leading digital freight platform, at the moment sennder is shifting from buy-and-build to outcome-driven and AI-native.
- 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.
Sennder values diversity, humility, and passion. We welcome applications from individuals who may not meet every qualification listed but share our ambition and drive to make an impact. If you’re excited about this role, we encourage you to apply.
Similar Jobs
Artificial Intelligence • Cloud • Computer Vision • Hardware • Internet of Things • Software
Generate sales pipeline for Samsara’s EMEA business through personalized outbound phone, email, and LinkedIn outreach. The role involves making 60+ daily prospect calls, maintaining Salesforce records, becoming a product expert, attending trade shows, and collaborating with Account Executives. Successful representatives can progress through Samsara’s ADR program toward an Account Executive role.
Top Skills:
Internet Of Things (Iot)LinkedInLushaSaaSSalesforceSalesloft
Cloud • Information Technology • Security • Software • Cybersecurity
Own and expand a portfolio of large enterprise accounts in Germany by identifying new use cases for Zscaler’s Zero Trust platform. Develop multi-year account plans, generate pipeline, lead executive sales engagements, coordinate cross-functional teams and channel partners, follow a structured sales methodology, and maintain forecast accuracy. The role focuses on expanding existing customer relationships, increasing platform adoption, and securing long-term strategic partnerships.
Top Skills:
Ai Workload ProtectionAi/MlCloud SecurityEnterprise SoftwarePredictive Sales AnalyticsSaaSSaseZero Trust Exchange
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Biotech • Pharmaceutical
Leads measurement and product marketing for eight enterprise AI platforms. Builds shared KPI, taxonomy, scorecard, data-quality, and value-realization frameworks; translates usage and outcome data into executive insights and investment guidance. Oversees positioning, internal launches, campaigns, enablement, adoption, and audience segmentation. Partners across product, engineering, data, communications, and business teams while building and managing teams responsible for analytics, marketing, and communications.
Top Skills:
Ai PlatformsBusiness IntelligenceDashboardsData ContractsData FabricData VisualizationEvent TaxonomyExperimentationKnowledge GraphsKpi FrameworksOkr PlatformsProduct AnalyticsTelemetry
What you need to know about the Montreal Tech Scene
With roots dating back to 1642, Montreal is often recognized for its French-inspired architecture and cobblestone streets lined with traditional shops and cafés. But what truly sets the city apart is how it blends its rich tradition with a modern edge, reflected in its evolving skyline and fast-growing tech industry. According to economic promotion agency Montréal International, the city ranks among the top in North America to invest in artificial intelligence, making it le spot idéal for job seekers who want the best of both worlds.
Key Facts About Montreal Tech
- Number of Tech Workers: 255,000+ (2024, Tourisme Montréal)
- Major Tech Employers: SAP, Google, Microsoft, Cisco
- Key Industries: Artificial intelligence, machine learning, cybersecurity, cloud computing, web development
- Funding Landscape: $1.47 billion in venture capital funding in 2024 (BetaKit)
- Notable Investors: CIBC Innovation Banking, BDC Capital, Investissement Québec, Fonds de solidarité FTQ
- Research Centers and Universities: McGill University, Université de Montréal, Concordia University, Mila Quebec, ÉTS Montréal
