Are you passionate about using cutting-edge AI to shape the future of sustainable agriculture? Do you combine a strong foundation in machine learning with a knack for creative problem-solving? Radicle Crops is looking for a pioneering Machine Learning Engineer to help transform our breeding company into a fully data-driven enterprise.

ABOUT THE ROLE

At Radicle Crops, our groundbreaking F1 Hybrid Breeding system has unlocked unprecedented possibilities for quinoa productivity. We believe the next leap forward lies at the intersection of data, biology, and artificial intelligence. As our Machine Learning Engineer, you will spearhead the design, implementation, and optimization of AI-driven tools that will define how our breeding decisions are made. You will enable earlier, more accurate selections from rich phenotypic data, driving a genuinely computational approach to guiding crop evolution.

This role offers a rare chance to push the boundaries of classical breeding using state-of-the-art deep learning phenomic tools. You will work within Project PHENOM, a high-profile public-private initiative with the Artificial Intelligence Group at Wageningen University. Together, we are developing deep learning methods to extract biologically meaningful insights from large-scale, complex single-plant image datasets. You won't just build models; you will generate the precise embeddings that capture how our unique quinoa genetics interact with diverse environmental stressors. By using AI to disentangle heritable traits from environmental noise, your code will directly dictate how Radicle Crops selects the next generation of climate-resilient, high-yield F1 hybrids. You will radically raise the accuracy of every prediction and selection we make.

KEY RESPONSIBILITIES

· Foundation Model Development: Develop, deploy, and optimize training and inference code for self-supervised (SSL) foundation models capable of extracting structure from complex single-plant datasets.

· Embeddings & Downstream Tasks: Generate and refine embeddings that capture multi-temporal phenotypic variation and environmental responses, moving beyond conventional phenotyping.

· Data Engineering: Design preprocessing and feature engineering pipelines to handle large-scale, multi-modal imagery (drone, satellite, and sensor data).

· Cross-Functional Collaboration: Partner closely with breeders, data scientists, and academic researchers at Wageningen University to translate deep learning insights into functional breeding tools.

· Culture & Innovation: Champion a robust data-driven culture and modern MLOps best practices within Radicle Crops while staying ahead of the curve in SSL and computational biology applied to plant breeding.

QUALIFICATIONS

· Education: MSc or PhD in Artificial Intelligence, Computer Science, Computer Vision, or a related quantitative field (or equivalent practical experience).

· Core Tech Stack: Strong Python programming skills with hands-on experience in modern deep learning frameworks (e.g., PyTorch).

· Domain Expertise: Solid understanding of computer vision architectures, ideally with exposure to self-supervised learning (SSL), foundation models, or multi-temporal/remote sensing data.

· Software Engineering: Familiarity with Git, code reviews, and collaborative software development workflows.

· MLOps & Deployment: Proven experience taking machine learning models from initial prototype to production—ideally in an agile, small-team, or startup environment.

· Mindset: Strong problem-solving skills, a high degree of autonomy, a passion for bridging the gap between deep learning and biological insights, and a deep desire to dive into the unknown.

WHAT WE OFFER

· Impact & Ownership: The rare freedom to build a foundational digital layer for a new crop, with significant autonomy to steer your projects and the future of our breeding program.

· Competitive Compensation: A base salary tailored to your expertise; indicatively €4,500–€6,500 gross per month, depending on experience and seniority (pending final budget approval). A competitive pension plan and benefits package to back your long-term personal and financial growth.

ABOUT RADICLE CROPS

Radicle Crops is an innovative plant breeding startup focused on making quinoa a universally accessible food source. Thanks to its climate resilience and exceptional nutritional profile, quinoa provides a unique opportunity for farmers worldwide to cultivate high-quality, gluten-free protein on marginal lands.

Spun out from Wageningen University & Research (WUR) -a global leader in plant and agricultural sciences- Radicle Crops operates at the absolute cutting edge of seed genetics and breeding technology. Built upon WUR’s foundational quinoa breeding program and technology stack, we maintain a deep, ongoing partnership with the university, combining a bold, creative startup mindset with world-class scientific backing to redefine sustainable agriculture.

WHY JOIN US?

We aren’t just optimizing an existing process; we are building a completely new food system from scratch. Quinoa is a uniquely climate-resilient crop with enormous untapped potential, and by building the global quinoa seed industry from the ground up, we’ve already shown what's possible when scientific rigor meets startup speed. We are the agile underdog that carved out a whole new category and now, we want to redefine what AI can do for plant breeding.

This isn't a role for someone looking to maintain legacy systems. We want someone hungry to question established methods, challenge traditional breeding and agronomic paradigms, and rewrite the rules of the industry.

As an early-stage member of our team, you will have the autonomy to shape our ML practices from day one, deploying your models directly into a live, real-world breeding program. You will bridge the gap between scrappy startup execution and world-class academic rigor, collaborating closely with leading minds in AI at Wageningen University to turn cutting-edge theory into tangible, global impact.

If you are up for the challenge, send your motivation letter and CV to info@radiclecrops.com by July 31, 2026.

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