Senior Machine Learning Engineer (m/f/d) - GeoAI for Humanitarian Applications

• *HeiGIT (Heidelberg Institute for Geoinformation Technology)**

As a nonprofit research institute, HeiGIT (Heidelberg Institute for Geoinformation Technology) bridges the gap between geoinformatics research and real-world applications, developing open-source solutions that address societal, environmental, and humanitarian challenges. Our Geoinformation for Humanitarian Aid team uses state-of-the-art machine learning and innovative digital technologies to support humanitarian organizations across the disaster management cycle, from risk assessment and preparedness to response. Working closely with our partners, we see firsthand how our work makes a difference on the ground.

We are looking for a Senior Machine Learning Engineer, with focus on GeoAI for Humanitarian Applications, to join our team in Heidelberg as soon as possible. The position is available full-time or part-time (50–100%) and requires at least 50% on-site presence in Heidelberg. The position is initially a two-year fixed-term contract with the option to extend.

• *Your day-to-day work with us**
• Identify, design and evaluate ML and AI approaches for geospatial, Earth observation and unstructured data (e.g. multimodal data fusion), and decide with the team which methods best fit humanitarian challenges
• Keep track of the state of the art in AI and turn new ideas into prototypes and products
• Develop and deploy ML models and data pipelines that are reliable, ready for real-world use and released as open source
• Help shape the technical direction of our work and share your methodological expertise with the team through coaching and co-learning
• *What sets you apart **
• A Master's degree or PhD in Geoinformatics, Earth Sciences, Geography, Computer Science, Physics, Mathematics, or a related field,with several years (ideally 5+) of professional experience developing and deploying ML solutions in industry or applied, project-based settings
• Strong knowledge of modern machine learning and deep learning methods, including experimental design, model evaluation, and the assessment of data quality, bias, and uncertainty
• Strong software engineering and MLOps skills (e.g. Python, PyTorch and/or TensorFlow), including experience deploying ML models (e.g. with Docker)
• Experience working with geospatial data (e.g. OpenStreetMap, street-level imagery, or remote sensing) and unstructured data, including LLM-based approaches
• Experience in research or innovation-driven projects, with a structured, evidence-based approach to solving complex problems and exploring new methods
• Very good English communication skills, a collaborative mindset, and enthusiasm for sharing knowledge, mentoring others, and contributing to meaningful societal impact
• *Here's what you can look forward to**
• **30 days of vacation (on a 5-day workweek) and additional days off **- for true relaxation and more free time
• **Flexible work arrangements** - with flex time and the option to work remotely part of the time. We expect you to work on-site at our Heidelberg office at least 50% of your working time
• **Freedom to shape your work & professional development** - a high degree of autonomy, short decision-making paths, and personalized professional development opportunities
• **More for you** – attractive subsidies for things like fitness, daycare, jobticket, and bike leasing, as well as capital-forming benefits, employer-sponsored retirement plan, and subsidized meals
• **A job with purpose and impact **– topics at the intersection of science, education, and social relevance
• *Join our team and help shape technologies that make a difference**

We look forward to receiving your application - including a cover letter, resume and certificates - through our Softgarden career portal. Please provide evidence of your track record in developing ML solutions, such as links to code repositories (e.g. GitHub, GitLab), deployed applications or publications. If your work isn't publicly available, please add a short description (max. one page) of one or two projects you were responsible for, including your role, the technologies used and the outcome.Please provide evidence of your track record in developing ML solutions as a separate document.

• *Clicking “Apply Online” will redirect you there.**

If you have any questions, Sabrina Marx and Marcel Maurer will be happy to assist you:

_We are committed to equal opportunity and welcome applications from everyone, regardless of age, background, gender, sexual identity, religion, or disability._