We’re a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
You will build and maintain the infrastructure for the Bayesian platform and develop CI/CD to enable other team members such as software engineers, data scientists, etc. to accelerate their development will drive expansion of our clinical AI/ML module offerings, health system enterprise-wide implementations, and revenue growth.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
What you’ll do
As an Infrastructure Engineer, you will build and maintain the networking and infrastructure for the Bayesian platform and develop CI/CD pipelines to enable other team members such as software engineers, data scientists, etc. to accelerate their development. This role is crucial to drive expansion of our clinical AI/ML module offerings, health system enterprise-wide implementations, and revenue growth.
Responsibilities
Design cost-optimized, fault-tolerant infrastructure for scale: Propose enhancement to our infrastructure design to enable us to expand our client base and deploy new products on our platform while managing cloud costs and ensuring reliability.
Streamline development and deployment: Define a branching and promotion strategy that allow us to comply with the regulatory change control process. Build and maintain CI/CD pipelines using GitHub for automated testing and deployment.
Establish and evangelize infrastructure best practices: Create infrastructure guidelines and templates such as Terraform modules, and educate team members in leveraging them.
Infrastructure support and maintenance: Continuous monitoring of system performance and reliability, and apply software upgrades accordingly. Collaborate with other team members in troubleshooting infrastructure issues and optimize performance.
Secure infrastructure: Partner with SecOps engineer to implement security best practices complying with HIPAA, HITRUST, FDA, and client requirements.
AI Ops Platform Architecture: Architect and build a secure, internal AI Ops platform to safely host and manage AI/ML agents for infrastructure and DevOps optimization.
Minimum qualifications
5+ years of experience building and operating production cloud infrastructure on AWS as a DevOps, Infrastructure, Site Reliability Engineer, or similar role.
Proficient with Kubernetes, preferably with EKS, including cluster bootstrapping and day-2 ops.
Strong operational knowledge of relational databases such as PostgreSQL/MySQL (backups, failover, performance tuning).
Deep expertise in Terraform (or equivalent IaC) and an eye for building clean and scalable modules.
Familiarity with observability tools, particularly the Datadog
Experience building infrastructure with sensitive data that contains PHI/PII.
Knowledge of CI/CD pipelines, preferably with CircleCI
Excellent communication skills and a proven ability to collaborate with cross-functional teams (e.g., engineering, data science) to translate requirements into robust technical solutions.
Experience handling ambiguity and uncertainty in a startup.
Preferred qualifications
Experience with using AI agents to optimize infrastructure management or DevOps workflows.
Experience with disaster recovery or business continuity plans.
Experience with multi account, multi cluster topologies.
Experience building systems in healthcare, life sciences, or similarly regulated industries
Chaos engineering or game-day facilitation.
Experience implementing and maintaining a GitOps framework.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Listed by Bayesian Health for a position based in the United States. Employers on this board attest they are hiring domestically.
BAYESIAN HEALTH, INC.
Software Engineer, Full Stack
Location
Remote - US Only
Employment Type
Full time
Location Type
Remote
Department
Engineering
Overview
Application
Software Engineer, Full Stack
In Brief
We’re a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
You will work closely with product managers, clinicians, data scientists, and other software engineers to build world-class clinical AI/ML products with direct positive impacts to frontline users within leading enterprise health systems.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What you’ll do
As a Software Engineer, you will be instrumental in the development and deployment of our clinical AI/ML products within leading enterprise health systems, involving close collaboration with product managers, clinicians, data scientists, and other engineers. Your contributions will be critical for expanding our product offering, directly impacting the company's revenue growth.
Responsibilities
Full Stack Product Ownership: Design, develop, test, deploy, and maintain robust and scalable full-stack clinical AI modules in production.
AI-Native Development: Leverage AI coding tools (e.g., Claude Code, Cursor) to rapidly build an end-to-end application in production quality grade and AI agents to optimize testing, debugging, and production maintenance.
Technical Design and Scoping: Partner with product managers, clinical, data scientists, and other software engineers to integrate our AI insights into intuitive and seamless clinical workflows.
Product Quality: Develop comprehensive and robust automated end-to-end tests to ensure platform and application functional integrity, meeting the requirements of enterprise health systems and regulatory.
Minimum qualifications
BS in Computer Science or other relevant technical discipline.
3+ years of experience building and maintaining scalable and reliable full stack applications in production using modern front-end technologies (React and Typescript preferred).
3+ years experience in developing and deploying end-to-end applications on a cloud platform (AWS preferred) powered by relational databases (e.g., Postgresql, MySQL, etc.) or cloud-based storages.
Experience with leveraging AI coding tools (e.g., Claude Code, Cursor, Codex) across the design, development, testing, and deployment lifecycle.
Experience handling ambiguity and uncertainty in a startup.
Preferred qualifications
Experience shipping AI/ML products in healthcare and/or at startups.
Experience working cross-functionally with clinicians to align on workflow and product functionality expectations.
Experience with health data, integration with electronic health records (EHR) systems, and health IT interoperability standards.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
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BAYESIAN HEALTH, INC.
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BAYESIAN HEALTH, INC.
Software Engineer, Analytics
Location
Remote - US Only
Employment Type
Full time
Location Type
Remote
Department
Engineering
Overview
Application
Software Engineer, Analytics
In Brief
We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
You will lead the development of our clinical AI/ML product analytics infrastructure, frameworks, and tools to enable our client success, product, clinical, and technology teams to uplevel our decision making through better insights.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What you'll do
As a Senior Software Engineer, Analytics, you will work closely with client success, product managers, clinicians, data scientists, and other software engineers to build infrastructure, frameworks, and tools to improve client analytics, facilitate clinical case reviews, and support product investigation. This role is crucial to provide internal visibility into product performance that will drive expansion of our clinical AI/ML module offerings and revenue growth.
Responsibilities
Product performance monitoring and optimization: Partner with client success and clinical product subject matter experts to implement the infrastructure, queries, and automation to monitor the KPIs and success metrics of our products across multiple clinical domains and clients.
Clinical case review and investigation: Build frameworks and tools to empower our clinical team to independently review and investigate clinical cases reported by our clients and identify cases with certain criteria that need further evaluation.
Data platform and analytics technical foundations: Propose and implement foundational improvements and innovations to boost our data platform scalability with expanding products and clients and uplevel our team analytics capabilities.
Drive product analytics development cross-functionally: Work closely with Client Success, Clinical, Product, Data Science, and Engineering to drive alignment on product analytics at the company level.
Minimum qualifications
BS in Computer Science or other relevant technical discipline.
5+ years of experience in building scalable, secure analytics infrastructure and tools on a cloud platform (preferably AWS) to produce monitoring metrics and investigational data from complex data models and queries for live products and customers.
Proficient in Python and SQL.
Deep knowledge in modern data and analytics technologies, such as cloud-based data warehouses, transformation frameworks (e.g. dbt), workflow orchestration tools, and BI tools like Tableau or Quicksight, and keen ability to integrate with existing infrastructure to enhance capabilities.
Experience working with sensitive data that contains PHI/PII.
Excellent communication skills and a proven ability to collaborate with cross-functional teams (data science, product, clinical) to translate requirements into robust technical solutions
Preferred qualifications
Experience in leveraging LLMs in distributed data processing and analytics systems.
Experience building analytics technology for clinical/health data.
Experience handling ambiguity and uncertainty in a startup.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Apply for this Job
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Listed by Bayesian Health for a position based in the United States. Employers on this board attest they are hiring domestically.
BAYESIAN HEALTH, INC.
Senior/Staff Machine Learning Data Scientist
Location
Remote - US Only
Employment Type
Full time
Location Type
Remote
Department
Data Science
Overview
Application
Senior/Staff Machine Learning Data Scientist
In Brief
We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
TLDR: Independent end-to-end model development with ability to work cross-functionally with Clinical, Engineering, and Product to clarify and prioritize specifications and features for our life-saving AI models.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
Read more about our recent publication in Nature Medicine that associates our products with lives saved.
What you’ll do
As a Senior/Staff Machine Learning Data Scientist, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren’t afraid to get your hands dirty by writing data mapping code, debugging a specific patient case by following patient data as it moves through our AWS services, or improving the timeliness of your model’s predictions by reading and writing production-grade Python and SQL code.
Responsibilities
Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods
Productionizing: The same models that you develop with production-grade Python
Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploy production-grade Python code to implement those strategies
Cross-Functional Alignment: Data Science for storytelling – understand model performance and metrics, and present this to technical and non-technical users, both internally and externally
Minimum qualifications
Ph.D. in a relevant field plus 3+ years experience shipping ML based software products
Experience owning your ML models from prototyping to production, especially real-time algorithms that update dynamically across time
Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems
Track record of using statistics and performance metrics to compare end-to-end ML and product performance
Preferred qualifications
Experience shipping breakthrough or 0-1 products from end to end, interpreting and leveraging State-of-the-Art methods to do so
Experience using messy clinical and health data to design new products for large Health Systems
Experience with any of the following: PyTorch, PySpark, HL7, FHIR, EHR, time series data, signal processing, MLFlow, anomaly detection, Bayesian statistics, quantile regression, time-series forecasting
You bring passion and enthusiasm to your work, and are excited to join a growing team to Get Stuff Done and save lives!
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Apply for this Job
Powered by
Privacy PolicySecurityVulnerability Disclosure
Listed by Bayesian Health for a position based in the United States. Employers on this board attest they are hiring domestically.
We’re an early-stage startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.
Part Data Scientist (building models), part Applied Scientist (productionizing models), and part MLE (deploying, maintaining), also known as “Full Stack Data Scientist” – someone who wants to own the end-to-end effectiveness of their real-time models in a live, clinical AI product.
Who We Are
Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.
We’re funded by top tier tech and biotech investors: Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.
As a Staff Machine Learning Engineer, you are not satisfied with training and tuning ML models that predict clinical conditions in patients; you also want to own the effectiveness of your model in the real world. In practice, that means you aren’t afraid to get your hands dirty by writing data mapping code, debugging a specific patient case by following patient data as it moves through our AWS services, or improving the timeliness of your model’s predictions by reading and writing production-grade Python and SQL code.
Responsibilities
Model Prototyping: Develop and tune innovative, new ML models and labeler systems based on deep understanding of clinical use cases and state-of-the-art ML methods.
Productionizing: The same models that you develop with production-grade python.
Deploying: Identify strategies for improving our production ML-based systems, and write, debug, and deploying production-grade Python code to implement those strategies.
MLOps: Build infrastructure that enables ML model development and deployment in production systems.
Minimum qualifications
Ph.D. in a relevant field plus 3+ years relevant experience, or a relevant Master’s degree and 5+ years experience shipping ML based software products.
Experience owning your ML models from prototyping to production.
Experience writing production-grade Python and SQL code to implement and evaluate ML models in production systems.
Experience using MLOps tools such as SageMaker and MLFlow.
Preferred qualifications
Experience going 0-1 and shipping high impact AI/ML products.
Experience building solutions within healthcare and/or familiarity working with messy health data.
Experience working with enterprise customers, and the agility and responsiveness they require.
Comfortable interpreting / leveraging state-of-the-art peer-reviewed methods or tools in designing your approach.
Excitement for Bayesian’s mission and being a bar raiser so we can accelerate the pace at which we create value.
Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.
Listed by Bayesian Health for a position based in the United States. Employers on this board attest they are hiring domestically.
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