Our Munich-based team near Sendlinger Tor brings together backend engineers, frontend developers, ML specialists, and geospatial analysts working at the intersection of enterprise software, climate data, and AI.

About The Role As Team Lead Machine Learning, you will own the ML team and the technical platform that powers our geospatial analytics. This is a hands-on leadership role: you will drive the development of production ML systems while building and growing the team around you.

Your work will span the full model development lifecycle. You will push forward our established, large-scale production system — improving the deforestation detection algorithm that monitors thousands of farms daily, engineering new deep learning models that generalize across geographies, and building the tools, platform, and processes that let the team iterate quickly and ship reliably. You will also champion the development of new analytics products as we expand what our platform can do.

This role requires someone who communicates clearly, aligns technical decisions across ML, product, and engineering, and leads by shipping. You will set the direction for how we develop, evaluate, and deploy models — and you will make the team around you more productive by building the right infrastructure and creating shared understanding of what matters and why.

Your Responsibilities

• Build and grow a high-performing ML team
• Align technical decisions across ML, product, and engineering
• Drive hands-on problem solving across our large-scale production system — getting models to work, shipping them, and iterating fast
• Own the full model development lifecycle, from research and prototyping through deployment, monitoring, and maintenance
• Architect a scalable ML platform that enables rapid experimentation and reliable production releases
• Champion the development of new analytics products within the team
• Design and implement geospatial analytics using state-of-the-art deep learning techniques and statistics
• Establish clear decision criteria for model development, ensuring alignment across the team and with product requirements

Your Experience You may be a good fit if you:

• Bring a strong quantitative background with an advanced degree (MSc or PhD) in computer science, engineering, mathematics, remote sensing, or similar
• Have advanced programming skills in Python and strong proficiency with deep learning frameworks (PyTorch/TensorFlow) and modern architectures. Besides that you are familiar with MLOps tools (e.g., W&B) and high-performance compute environments (AWS, bare-metal)
• Have 5+ years of hands-on machine learning experience with a track record of shipping production-level systems. Additionally, you have 2+ years of experience leading a technical team, including hiring, mentoring, and setting direction
• Communicate with clarity - you align stakeholders and articulate technical decisions clearly, creating shared understanding across teams
• Are deeply technical - you get things to work quickly, solve problems pragmatically, and own systems end-to-end
• Have prior experience in a software company, shipping productized analytics at scale, and are comfortable in a fast-paced, high-growth environment
• Bring routine in working with petabytes of data and designing effective data processing tools and workflows
• Work effectively with AI-assisted workflows and coding tools
• Are fluent in English (C1+) and German (C1+)

Strong Candidates May Also Have

• Experience with modern computer vision architectures applied to problems such as segmentation, change detection, and time-series image data
• Experience working with remote sensing or satellite data (SAR, optical, LIDAR)
• Experience translating product requirements and complex regulatory needs into algorithmic, data-driven solutions

Join us for this and more... Representative projects

• Improve change detection in time-series satellite image data using supervised and unsupervised machine learning methods- Fuse multiple satellite modalities such as SAR, optical, and LIDAR in a streamlined data pipeline to enable near-real-time monitoring across thousands of supply chain locations
• Train or fine tune models across diverse geographies and land cover types
• Design and implement model evaluation and monitoring frameworks that give the team confidence in production performance and guide development priorities
• Build and scale the ML experimentation platform — tooling, compute infrastructure, and development workflows — to reduce iteration time from idea to production deployment
• Lead the development of a new analytics product, taking it from early research through production rollout and customer delivery

Benefits

• A purpose-driven mission tackling complex sustainability challenges while working alongside global industry pioneers at a fast-growing unicorn company
• Room for creativity through collaborative teamwork and an open communication culture
• Flexibility and team bonding with our hybrid work options
• Fuel for your growth journey, both personally and professionally
• Sustainable mobility options, promoting eco-friendly commuting solutions
• Fun team events and outings with our global teams
• Inspiring workspaces in Mannheim, Munich and Madrid