Senior Machine Learning Engineer (m/f/d)

Greenda is an early-stage Ag Tech startup backed by TDK, building the scientific backbone that makes pest management and integrated pest management (IPM) actionable for agri-technicians and farmers.

Our platform combines image-based crop diagnosis, pest prediction, and integrated pest management tools to deliver grounded, field-relevant intelligence at scale.

We are currently focused on permanent horticultural crops in Spain, with a roadmap to expand into new markets as our science and data infrastructure matures.

Why this role matters

As our Machine Learning Engineer, you will be responsible for transforming scientific knowledge and field data into intelligent decision-support systems that help farmers make better decisions every season.

Your work will span the full lifecycle of applied machine learning at Greenda; from improving AI-assisted crop diagnosis to designing entirely new machine learning models that recommend farm-specific Integrated Pest Management (IPM) strategies.

This is not a role where every problem already has an established solution.

Some challenges, such as image diagnosis, have clear technical pathways and well-defined evaluation metrics.

Others, such as learning optimal treatment strategies from weather, treatment history, pest pressure, and harvest outcomes, are still open scientific questions.

You will work in close partnership with the CSO, Lead Agronomist, and Data Scientist, but you will be the company's primary expert in machine learning.

Your judgement, scientific rigor, and ability to balance innovation with practical delivery will directly influence the future of Greenda's AI platform.

What you'll do

• Design and develop machine learning models that support farm-specific Integrated Pest Management (IPM) recommendations.
• Research and evaluate machine learning techniques capable of learning from treatment history, weather, crop development, pest observations, harvest outcomes, and future data sources.
• Design robust experimentation, benchmarking, and evaluation frameworks that enable evidence-based model development and continuous improvement.
• Work closely with the Lead Agronomist to translate biological and agronomic knowledge into computational representations.
• Collaborate with the Data Scientist to improve datasets and ensure high-quality model inputs.
• Communicate technical decisions, model performance, and trade-offs clearly to both technical and non-technical colleagues.
• Help shape Greenda's long-term machine learning strategy and identify opportunities where Greenda can build defensible intellectual property through novel computational approaches.
• Own the development and continuous improvement of Greenda's AI-assisted crop diagnosis capabilities.
• Design, evaluate, and improve prompt engineering strategies, retrieval systems, and future approaches.
• Measure and report diagnostic accuracy, robustness, and model performance.
• What we are looking for
• At least 6 years of professional experience in machine learning, including developing, deploying, and maintaining production-ready ML models.
• Advanced degree (MSc preferred; Ph D welcomed) in Machine Learning, Artificial Intelligence, Computer Science, Applied Mathematics, Statistics, Computational Biology, or a related quantitative discipline, or equivalent industry experience building and deploying machine learning systems.
• Comfortable working across the modern ML/AI stack; Python, common ML frameworks, LLM APIs, and cloud infrastructure; able to make sound tooling choices rather than defaulting to what you already know.
• Demonstrated experience designing approaches that are scientifically robust, commercially appropriate, and aligned with company growth stage with a a thoughtful approach to data responsibility and fairness, given this role's direct influence on how farmer field data is used.
• Demonstrated experience taking technical projects from ambiguity to production, demonstrating strong ownership, sound judgement, and reliable delivery throughout the process.
• Experience in agricultural sciences and/or the curiosity to learn and collaborate closely with domain experts.
• A track record of proactively sharing progress, surfacing risks early, inviting constructive challenges, and helping create an environment where good ideas can come from anyone on the team.
• A strong commitment to psychological safety, respectful collaboration, and supporting teammates through open communication, curiosity, and patience.
• Full professional proficiency in English.
• This role requires existing work authorization for Germany or the EU;
• As Greenda's first dedicated machine learning hire, you'll define how AI is built here, not inherit someone else's stack or roadmap.
• You'll work directly with the CSO on machine learning strategy from day one, with a clear path to lead and grow the ML/AI function as the team scales, including hiring and shaping the team under you.
• Competitive package
• Annual training and self-development budget to support continuous learning and career growth.
• Join an international, mission-driven team working on applied Ag Tech innovation.
• Empower small and medium farmers with next-generation Integrated Pest Management (IPM) protocols and accessible, applied-agriculture AI.
• One-week, fully funded "farm stay" experience: live and work on an organic farm to connect with real-world agriculture (self-organized, WWOOF-style).
• Company benefits including lunch, transport, and internet allowances.
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