• Training and evaluating deep learning models (vision, time series, neurodata, etc.)
• Building pipelines and infrastructure for experimentation and reproducibility
• Scaling ML workflows and managing real-world data
• Supporting research teams in fast-moving environments

You’re hands-on, collaborative, and excited by the idea of building the ML backbone of science-native AI systems.

• 🛠️ Strong ML engineering skills (Python, PyTorch, JAX, etc.)
• 📦 Experience working across diverse data types or scientific modalities
• 🔁 Good software habits: versioning, testing, clean code
• 🤝 Team-first mindset and ability to work across functions
• 🌱 Curiosity and desire to work in a science-driven environmentWill be communicated soon , potentially with different job descriptions for different roles