Member of Technical Staff, Causality
Core
Design and implement novel causal inference methods for treatment effect modeling and translate machine learning research into production-ready code for clinical AI tools.
Role type
Research IC causal inference engineer
Builds
Clinical AI tools for predicting patient outcomes and treatment response
Domain
Healthcare / Clinical AI / Causal Inference
Deliverable
production ML models
Required skills
Causal inference methods, Python, PyTorch, Deep learning, Statistics, Linear algebra, Probability, Machine learning, Observational data analysis, Randomized trial data analysis
Preferred skills
Survival analysis, Multi-modal learning, Domain adaptation, Model interpretability, Computational pathology, Medical data experience, Publications in A* conferences (ICML, ICLR, NeurIPS, CVPR)
Technologies
Python, PyTorch
Responsibilities
Design and implement novel causal inference methods for treatment effect modeling; Translate machine learning papers into production-ready code; Build robust model evaluation frameworks; Disseminate the results by co-authoring research papers and abstracts; Collaborate with a multidisciplinary team of engineers and scientists; Co-mentor junior members of the team
Seniority
Senior, hands-on IC
