About Proon-Tech

We’re a nature-tech startup working where software meets living systems - inside orchards, among trees that carry people’s livelihoods and support feeding communities 🍏🌳. What we do has cause and effect. Every decision, every cut, every model output can influence yield, income, and long-term ecosystem health.

That’s why we’re building the foundational platform for tree and orchard life cycle management, starting with one of the most demanding, high-skill operations in agriculture: pruning.

Pruning isn’t cosmetic. It’s structural. It determines how a tree grows, how much it produces, and how resilient it is over decades. We’re translating generations of pruning knowledge into machine learning, computer vision, and cloud-based tools — so this expertise can scale, propagate and compound.

We’re solving the labor and skill gaps in orchards, we are securing the entire supply chain—from the first cut of a branch to the "sensory bliss" of the consumer's first bite.

We’re turning land-based systems into anti-fragile assets that can withstand climate volatility through technological adaptation and precision.

At Proon-Tech, we’re building something that lives far beyond the screen toward our mission to ensure:

• the security of global Food Systems & supply chains
• ecosystem resilience
• climate-smart Infrastructure rooted in Regenerative Agriculture

Now we’re looking for someone who wants to help architect that intelligence.

🌱 About the role

As a Nature Architect – Machine Learning / AI Software Engineer Intern, you won’t just be “building a model.” You’re helping us further teach the AI system that automatically identifies tree branches that should be pruned — and integrate those models into a cloud-based pruning platform. Basically, teaching AI how to see trees the way skilled humans do — and how to support decisions that matter in the real world.

You’ll work closely with our CTO and Co-founder, Stefan, and with a nature engineer who brings field reality into the data. You’ll have the opportunity (if you want it) to step into orchards and see how your software behaves when light shifts, branches overlap, and biology refuses to be neat.

This is a paid role, and we’re looking for people who want to work with us — as collaborators, equals, and potentially long-term partners — not just check internship boxes. This is not a "screen-only" role. You’ll be building the intelligence layer that allows software to interact with organic material to drive literal improvement in nature.

What You’ll Do

You’ll work at the intersection of computer vision, ML model development, and backend/app integration using Google Cloud and Firebase, with strong domain support from an experienced nature engineer who will guide field data acquisition and annotation.

As part of the team, you’ll:

• Prototype and train ML/computer vision models to detect and classify branches to prune from images and/or sensor data
• Prepare and label datasets from orchard/tree imagery (cleaning, augmentation, basic analytics)
• Collaborate closely with a nature engineer supporting field data collection and annotation workflows
• Deploy and integrate models into the pruning application using Google Cloud + Firebase (Cloud Functions, Firestore, Storage, Firebase ML)
• Build and maintain APIs connecting the ML backend with mobile/web apps used in the field
• Document experiments and iterations so what we build is understandable, traceable, and improvable over time

⏳ Duration: 6 months

Open to extension or evolution based on mutual fit and contribution

🧠 The kind of person we want joining us:

You don’t need to know everything. You do need to care deeply about building things that work.

✅ Must-haves - Technically, you likely have:

• A BSc or MSc background (or current enrollment) in CS, AI, Data Science, or a related field
• Strong Python skills and hands-on experience with PyTorch, TensorFlow, or scikit-learn
• Basic practical computer vision experience (segmentation, detection, classification, preprocessing etc.)
• Experience with Google Cloud and Firebase (Firestore/Realtime DB, Cloud Functions, Storage, Auth, Firebase ML)
• Experience building or consuming REST APIs, and working on web/mobile projects (school, personal, or open-source)

⭐ Nice to Have

Bonus points for:

• On-device ML experience (TensorFlow Lite or similar)
• Familiarity with 3D data, point clouds, or depth cameras (agriculture/robotics context)
• Experience with Git/GitHub and CI/CD for ML or app projects

🧠 Mindset-wise:

• Curious, but also disciplined
• You like understanding why things work — and why they don’t
• Comfortable working independently in a remote, async setup, in your rhythm
• Interest in nature, agriculture, robotics, and / or precision agriculture tools / machinery
• Driven by contributing to something that will last 🌱

What We Offer

Paid role / partnership | Remote, with optional field work | Romania → EU → USA

• Work on a real-world AI product supporting sustainable orchard, forestry & vineyard management
• Direct experience in the field (EU/USA) seeing nature-tech in action on a global level
• Close, high-level mentorship with the founders
• Network of highly professional and knowledgeable global experts, organizations, universities & environments
• Flexible schedule compatible with universities
• Potential to extend into long-term collaboration or junior role based on performance + ESOP

🌍 The environment you’re stepping into

This is a high-stakes environment, not dramatic, but real.

Pruning decisions affect:

• orchard productivity and long-term structure
• farmer income and workforce planning
• resilience to climate stress and disease

Your work contributes directly to:

• food system security 🍎
• ecosystem resilience 🌍
• the future of skilled, tech-enabled green jobs

That responsibility is part of the role - and part of what makes it meaningful.

👉 How to Apply - if this resonates with you send us the elements below at connect@proon-tech.com

📌 Your CV

📌 Portfolio / GitHub

📌 2–3 sentences about an ML project you know deeply — one you could talk about half-asleep at 3 a.m., including what worked, what didn’t, and what you learned

Regenerative Agriculture Architect Internship | AI + Computer Vision | Google Cloud + Firebase |