🛠 Tech Stack

💼 About This Role

You'll lead ML-driven climate modeling at the intersection of hydrology, weather, and large-scale machine learning. Your work will shape next-generation prediction systems by integrating scientific process understanding with modern ML methods. This cross-functional role allows you to move between foundational research and applied execution.

🎯 What You'll Do

• Lead scientific and ML development for hydrology-aware climate modeling
• Define research priorities and evaluation strategies for environmental prediction
• Work with large-scale climate, weather, and remote sensing datasets
• Build reproducible workflows for data processing, model training, and validation

📋 Requirements

• PhD in machine learning, computational science, or related quantitative discipline
• 5+ years experience in climate ML or hydrologic modeling
• Demonstrated experience with ML-accelerated weather or climate models
• Strong programming in Python and experience with PyTorch

✨ Nice to Have

• Background in scientific ML, spatiotemporal modeling, or hybrid physics-ML methods
• Experience with AWS ecosystem for large climate datasets
• Experience leading cross-functional scientific efforts

🎁 Benefits & Perks

• 🧬 Work at a bioplatform innovation company that invents and builds companies
• 🌍 Impact on sustainability and human health through climate modeling
• 👥 Collaborate with top scientific minds and entrepreneurial leaders

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter screen· 30 min
2. 2Technical interview· 60 min
3. 3On-site interviews· Full day