Opportunity at
Bayesian HealthStaff Machine Learning Engineer
Bayesian Health seeks a Staff Machine Learning Engineer to join its team as a full-time, on-site employee. This organization operates as an early-stage startup backed by…
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About This Role
Bayesian Health seeks a Staff Machine Learning Engineer to join its team as a full-time, on-site employee. This organization operates as an early-stage startup backed by prominent investors including Andreessen Horowitz, Catalio Partners, LifeForce Capital, and the venture arm of the American Medical Association. Recognized by entities such as Forbes and the World Economic Forum, the company builds clinical AI products designed to deliver real-time data to nurses, physicians, and…
Job Description
Bayesian Health seeks a Staff Machine Learning Engineer to join its team as a full-time, on-site employee. This organization operates as an early-stage startup backed by prominent investors including Andreessen Horowitz, Catalio Partners, LifeForce Capital, and the venture arm of the American Medical Association. Recognized by entities such as Forbes and the World Economic Forum, the company builds clinical AI products designed to deliver real-time data to nurses, physicians, and care teams with the goal of improving patient outcomes.
This position functions as a blend of data scientist, applied scientist, and machine learning engineer, sometimes referred to as a full-stack data scientist. The ideal candidate wants total ownership over the end-to-end performance of real-time clinical models in a live production environment. Daily tasks extend beyond simple model training and tuning to include writing data mapping code, troubleshooting individual patient data pipelines within AWS services, and utilizing production-grade Python and SQL to enhance prediction speed.
Qualified individuals must hold either a Ph.D. in a relevant discipline alongside at least three years of pertinent experience or a relevant Master's degree combined with a minimum of five years of experience releasing machine learning software into production. Applicants are expected to manage machine learning models across their entire lifecycle, from initial prototype to operational deployment, while utilizing MLOps technologies like MLFlow and SageMaker.
Responsibilities
- Design and optimize novel machine learning models and labeler systems driven by clinical use cases and advanced methodologies
- Transform developed models into production-ready software using production-grade Python
- Plan deployment approaches for production machine learning architectures and write, troubleshoot, and release Python code to execute those plans
- Construct the underlying infrastructure required to support machine learning model development and operational deployment
Requirements
- Doctorate in a relevant technical field paired with three or more years of applicable experience, or a Master's degree with at least five years of experience delivering machine learning software
- Demonstrated history of managing machine learning models from the prototyping phase all the way to production
- Proficiency in producing high-quality Python and SQL code for implementing and assessing operational machine learning systems
- Working knowledge of MLOps platforms such as MLFlow and SageMaker
Qualifications
- Background in launching zero-to-one high-impact artificial intelligence and machine learning solutions
- Past involvement creating solutions within the healthcare sector or handling complex, unstructured health data
- Experience interacting with enterprise clients in a responsive and agile manner
- Ability to interpret and apply state-of-the-art peer-reviewed techniques and tools to design solutions
- Passion for the mission of Bayesian Health and a drive to accelerate value creation
Core Skills
Frequently Asked Questions
What is the employment type for this role?
This position is a full-time role.
What is the remote work policy for this position?
The posting indicates that the job is on-site, though specific geographic locations are not stated in the text.
What is the salary range offered?
The salary details are not specified in the job posting.
What education and experience are required to apply?
Applicants must possess either a Ph.D. in a relevant field with at least three years of experience, or a Master's degree with a minimum of five years of experience shipping machine learning software products.
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