Healthcare Neurosymbolic ML Engineer — Equity & Impact

Evidium, Inc.; San Francisco (CA); Hybrid; USD 140,000 - 190,000; Full time

Benefits offered by this job

Competitive compensation

Equity

Interdisciplinary team

Job summary

Evidium, Inc. is seeking a Machine Learning Engineer to develop predictive models from longitudinal healthcare data and deploy scalable ML pipelines. You will balance rigor, interpretability, and scalability while collaborating with clinicians, engineers, and product teams.

Join a collaborative, curious culture focused on transparent, clinically grounded AI. Opportunities to publish, shape research direction, and influence policy decisions are available.

Qualifications

• Strong background in statistical modeling or data science with longitudinal data.
• Proficiency in Python and ML ecosystems (PyTorch, JAX, NumPyro, PyMC).
• Experience taking models from research prototype to production.
• Bonus: clinical data terminologies and actuarial modeling.

Responsibilities

• Develop predictive models forecasting disease progression, utilization, and cost from temporal clinical data.
• Design interpretable ML solutions trusted by clinicians and actuaries.
• Research and prototype novel approaches using classical and modern ML.
• Implement robust, scalable ML pipelines for training, validation, and deployment in distributed compute environments.
• Collaborate 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.

Skills

Python

Temporal data

Production deployment

Statistical modeling

Survival analysis

Probabilistic methods

Tools

PyTorch

JAX

NumPyro

PyMC

Job description

Evidium, Inc. is seeking a Machine Learning Engineer to develop predictive models from longitudinal healthcare data and deploy scalable ML pipelines. You will balance rigor, interpretability, and scalability while collaborating with clinicians, engineers, and product teams.

Join a collaborative, curious culture focused on transparent, clinically grounded AI. Opportunities to publish, shape research direction, and influence policy decisions are available.