Machine Learning and AI Specialist-Associate Principal Scientist
Core
Design, build, and scale machine learning models for predicting properties and 3D structures of small and large molecule complexes to accelerate drug discovery.
Role type
Associate Principal Scientist, Machine Learning and AI Specialist
Builds
AI-powered tools for molecular design and decision-making in oncology R&D
Domain
Biopharmaceuticals / Computational Chemistry / Generative AI
Deliverable
production ML models
Required skills
Graph neural networks, Transformers, Diffusion models, Flow matching, Python, PyTorch, DeepChem, TensorFlow, Distributed computing pipelines, Containerization (Docker, Kubernetes), Protein-ligand complex prediction, Algorithmic benchmarking
Preferred skills
Protein structure prediction, Large-scale cloud computing, GPU acceleration, Peer-reviewed publications in machine learning
Technologies
PyTorch, TensorFlow, DeepSpeed, Horovod, MPI, Nvidia Apex/AMP, Docker, Kubernetes, DeepChem
Responsibilities
Design and implement AI architectures for molecular property and structure prediction; Build scalable distributed computing workflows; Lead protein co-folding and prediction workflows; Evaluate emerging computational methodologies and define best practices; Present complex results to multidisciplinary audiences; Publish in high-quality journals and present at conferences
Seniority
Associate Principal, hands-on IC with strategy influence
