Applied Scientist

Evidium’s mission is to scale medical knowledge and create reliable AI for the health benefit of every person.

We’re developing a new class of neurosymbolic AI systems, combining statistical learning with structured medical knowledge to create transparent, clinically grounded models. Our early adopters include health systems and insurers using Evidium’s technology to improve patient-level foresight, evidence deployment, and prediction.

Our culture is collaborative, curious, and first-principles-driven. We prize individuals who are not only excellent implementers, but original thinkers — people who can reason clearly about complex systems and translate that understanding into production-quality solutions.

The Role

We’re looking for Machine Learning Engineers who thrive at the intersection of data science, modeling, and software engineering. You’ll design and implement models that learn from longitudinal healthcare data, balancing rigor, interpretability, and scalability.

This is a rare opportunity to work on foundational modeling challenges in healthcare, where your work will directly inform clinical, actuarial, and policy decisions.

Responsibilities

• Develop predictive models that forecast disease progression, utilization, and cost from temporal clinical data (claims, EHR, lab, pharmacy, etc.)
• Design interpretable and explainable ML solutions that can be trusted by clinicians, actuaries, and decision-makers
• Research and prototype novel approaches, leveraging both classical and modern ML
• Implement robust, scalable ML pipelines for training, validation, and deployment in distributed compute environments
• Collaborate cross-functionally with data engineers, clinicians, and product teams to align models with real-world healthcare needs
• Communicate findings and methodologies clearly through visualizations, documentation, and technical presentations
• EDA, working closely with domain experts

Requirements

• Strong background in statistical modeling, machine learning, or data science, ideally with experience in temporal or longitudinal data
• Proficiency in Python and ML ecosystems (PyTorch, JAX, NumPyro, PyMC, etc.)
• Demonstrated ability to take models from research prototype to production
• Familiarity with probabilistic methods, survival analysis, or Bayesian inference is a plus
• (Bonus) Experience with clinical data and terminologies (ICD, CPT, SNOMED CT, LOINC, etc.)
• (Bonus) Exposure to actuarial modeling, claims forecasting, or risk adjustment methods

What We Offer

• Competitive compensation and equity
• Work alongside an interdisciplinary team of researchers, engineers, and clinicians
• Direct impact on the development of healthcare’s next-generation predictive infrastructure
• Opportunities to publish, co-author patents, and shape the research direction of Evidium

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