Founding Scientist — Generative & Causal ML Healthcare

Neura Augma (Neau AI) is an autonomous intelligence research and product company focused on making autonomous intelligence as trusted as the healthcare experts it serves. Our product, HALE, is an execution layer for healthcare AI designed to solve one of the field’s foundational challenges: the lack of a reliable health data foundation for practical, scalable, autonomous AI.

This founding member will own the core AI/ML systems powering our synthetic intelligence capabilities, designing and building models that generate realistic, high-fidelity scenarios for complex real-world environments. The role blends applied machine learning, data systems thinking, and product intuition, with responsibility for turning new ideas into robust, production-ready features. This is a equity-forward, founder-type role with the potential to grow into leadership, with flexibility for part-time or full-time engagement depending on fit and stage.

Academic researchers and postdocs with relevant ML, healthcare AI, or data systems experience are welcome to apply.

• Design models for structured, temporal, multimodal, and causal data
• Build, train, and evaluate ML architectures and models
• Support distributed or federated learning across multi-site or cross-boundary settings
• Develop privacy-preserving training and evaluation methods
• Establish reproducibility, versioning, and testing standards
• Optimize models for constrained environments (limited compute, memory, etc.)
• Help shape product direction through technical decisions

• Strong experience in generative modeling, data fusion, and multimodal models
• Comfort with real‑world datasets and irregular time‑series
• Experience with EHR standards such as OMOP, FHIR, or similar frameworks
• Familiarity with medical ontologies (SNOMED, LOINC, RxNorm) or knowledge graphs
• Interest in learning hybrid classical-quantum methods (Qiskit, Penny Lane)
• Ability to translate research concepts into production‑grade code
• Entrepreneurial mindset: thrives in ambiguity, builds fast, iterates fast

You prototype and deliver ML architectures for realistic, high‑fidelity data modeling and privacy preservation, bridging research and production while supporting scientific collaboration.