Description:

Bayesian Health is an early-stage startup focused on making healthcare proactive by providing real-time data to healthcare professionals to save lives.
The role involves independent end-to-end model development and collaboration with Clinical, Engineering, and Product teams to clarify and prioritize specifications and features for AI models.
The company aims to improve patient outcomes by empowering clinicians with insights for better decision-making at the point-of-care.
Responsibilities include developing and tuning innovative ML models, productionizing these models with production-grade Python, and identifying strategies for improving production ML systems.
The candidate will also be responsible for understanding model performance and metrics and presenting findings to both technical and non-technical audiences.

Requirements:

A Ph.D. in a relevant field and at least 3 years of experience in shipping ML-based software products are required.
Candidates must have experience owning ML models from prototyping to production, particularly real-time algorithms that update dynamically.
Proficiency in writing production-grade Python and SQL code for implementing and evaluating ML models in production systems is necessary.
A track record of using statistics and performance metrics to compare end-to-end ML and product performance is essential.

Bayesian Health offers equal employment opportunities and prohibits discrimination and harassment of any type.
The company provides a supportive work environment that encourages collaboration and innovation.
Employees are part of a diverse team committed to saving lives and improving healthcare delivery through data-driven insights.

Skills