Healthcare ML/Causal Inference Engineer at VC-backed precision healthcare startup

Join a high-impact team as a founding-level engineer building an AI platform that transforms oncology treatment. You will leverage a massive proprietary dataset of 142 million clinical records to develop causal inference models. Your work directly enables physicians to make safer, data-driven decisions, sparing patients from unnecessary procedures and improving survival outcomes through superhuman precision.

VC-backed precision healthcare startup

• Design and implement advanced ML models and causal inference techniques to understand treatment efficacy from complex EHR timelines.
• Build and deploy 70B+ parameter multimodal systems that synthesize imaging, genomic, and clinical data for medical reasoning.
• Architect robust evaluation frameworks to ensure clinical safety and accuracy for high-stakes healthcare decision-making.

• PhD-level research experience or equivalent technical excellence in ML and causal inference from a top-tier global institution.
• Proficient in Python, PyTorch, and large-scale data processing with a track record of shipping models in high-stakes environments.
• Founding engineer DNA with the ability to thrive in ambiguity and a deep personal commitment to transforming cancer care.

• Rare access to a massive, proprietary multimodal data moat including longitudinal radiology, pathology, and genomic records.
• Founding-level impact as hire #7, working directly on core models used by oncologists at the bedside.
• Backed by top-tier VCs who were early investors in world-leading AI and fintech giants.