Bayesian Health

Software Engineer, Application Integration 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. Join us in transforming healthcare from reactive to proactive. You’ll spearhead the engineering effort to build the bridge between massive, complex Electronic Health Record (EHR) systems and the Bayesian platform, delivering critical, real-time insights to help clinicians save lives. 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 You will be at the forefront of a high-impact engineering mission, building the bridge between the Bayesian platform and the clinical workflows inside massive, complex Electronic Health Record (EHR) systems, delivering the real-time lifesaving insights that clinicians rely on. Working directly with our health system clients' EHR and clinical informatics teams, you'll bring our clinical insights to the point of care — in the right workflow, at the right moment — empowering care teams to make the best decisions for their patients. Each integration is a partnership. An Implementation Lead owns the client relationship and project management; a Clinical Integration owns clinical workflow design and training. You own the technical workstream — which means you're the engineer in the room. When a clinician says the alert didn't fire for a patient, you have thirty minutes and their full attention to trace it from the EHR launch context through the API to the underlying data, and tell them what happened. Responsibilities Clinical Workflow Integration: Extend and configure the full-stack application across the EHR integration surface, coordinating with client EHR and clinical informatics teams, to deliver Bayesian's clinical insights to clinicians. Integration Testing & Troubleshooting: Implement automated integration tests and work directly with client technical teams and frontline clinicians during integration testing to investigate and resolve issues, ensuring smooth and timely integrations. Production Deployment & Go-Live: Execute the deployment process in close collaboration with the client's technical team, ensuring all configurations and builds for the application and workflow are successfully promoted to production for a seamless launch. During go-live week, you will serve as the technical point of contact for any application integration issues, both internally and with the client's teams, providing clear status updates to cross-functional partners so they can effectively manage client communication. Integration Tooling & Automation: Develop frameworks and tooling, leveraging LLMs and automation, to increase the efficiency and velocity of our platform integrations as we scale. Cross-Functional Collaboration: Work alongside an Implementation Lead, Clinical Integration, and the client's technical teams to align the application integration workstream with the overall integration effort. Minimum qualifications BS in Computer Science or equivalent practical experience 3+ years building and deploying full-stack applications into production, including integration with external APIs (React, TypeScript preferred) Strong ability to investigate and resolve application issues end-to-end Experience with cloud solutions (AWS, Azure, etc.) and relational databases (PostgreSQL, MySQL, etc.) in a production environment Experience writing automated integration and end-to-end tests for production systems Strong communicator with a demonstrated ability to collaborate across functions, working effectively with internal stakeholders, including Product Managers, to align on priorities and deliver results. Preferred qualifications Experience building EHR-embedded applications such as SMART on FHIR, CDS Hooks, or Epic launch integration. Experience rolling out production deployments, supporting systems through go-live via an on-call or support rotation, and triaging production issues Experience working with enterprise customers, and the agility and responsiveness they require. Experience building internal tooling or automation, including leveraging LLMs, to improve eng

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 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. Read more about our recent publication in Nature Medicine that associates our products with lives saved. 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 a

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.

Software Engineer, Data Integration 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. Join us in transforming healthcare from reactive to proactive. You’ll spearhead the engineering effort to build the bridge between massive, complex Electronic Health Record (EHR) systems and the Bayesian platform, delivering critical, real-time insights to help clinicians save lives. 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 You will be at the forefront of a high-impact engineering mission, building the bridge between massive, complex Electronic Health Record (EHR) systems and the Bayesian platform to generate real-time lifesaving clinical insights that clinicians rely on. Working directly with our health system clients' technical teams, you'll turn fragmented data into immediate, actionable clinical insights that empower care teams to make the best decisions for their patients. Each integration is a partnership. An Implementation Lead owns the client relationship and project management; a Clinical Integration owns clinical workflow design and training. You own the technical workstream — which means you're the engineer in the room. When a lab result isn't reaching the Bayesian platform for a patient, you have thirty minutes and the client's full attention to trace it from the inbound HL7 message through parsing, mapping, and ingestion, and tell them what happened. Responsibilities Data Integration & Ingestion: Partner with the client's technical teams to design and implement the data integration interface and ingestion pipelines that feed the Bayesian platform with real-time clinical data, powering insights that improve patient outcomes. Integration Testing & Troubleshooting: Implement automated integration tests at the data layer, and work directly with client technical teams during integration testing to investigate and resolve issues, ensuring smooth and timely integrations. Production Deployment & Go-Live: Execute the deployment process in close collaboration with the client's technical team, ensuring build and configuration for the data interface, ingestion, and mapping are successfully promoted to production for a seamless launch. During go-live week, you will serve as the technical point of contact for any data integration issues, both internally and with the client's teams, providing clear status updates to cross-functional partners so they can effectively manage client communication. Integration Tooling & Automation: Develop frameworks and tooling, leveraging LLMs and automation, to increase the efficiency and velocity of our platform integrations as we scale. Cross-Functional Collaboration: Work alongside an Implementation Lead, Clinical Integration, and the client's technical teams to align the data integration workstream with the overall integration effort. Minimum qualifications BS in Computer Science or equivalent practical experience 3+ years building and deploying data pipelines to production, including integration with external APIs (Python preferred) Strong ability to investigate and resolve data correctness problem end-to-end, across services, storage, and external data sources. Experience with cloud solutions (AWS, Azure, etc.) and relational databases (PostgreSQL, MySQL, etc.) in a production environment Experience writing automated integration tests for production systems Strong communicator with a demonstrated ability to collaborate across functions, working effectively with internal stakeholders, including Project/Product Managers, to align on priorities and deliver results. Preferred qualifications Experience with health data, integration with Electronic Health Records (EHR) systems, and Health IT interoperability standards such as HL7v2 and FHIR. Experience rolling out production deployments, supporting systems through go-live via an on-call or support rotation, and triaging production issues Experience working with enterprise customers, and the agility and responsiveness they require. Experience building internal tooling or automation, includ

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.

Senior Design Quality Engineer 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'll safeguard product quality for an FDA-cleared, AI-driven clinical platform, from design controls while we build, to complaint investigation once it's live in hospitals, to the quality system and regulatory record that hold it all together. 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, AI 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. Recent recognitions include Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, and BioTech AI Company of the Year. Read more about our peer-reviewed research in Nature Medicine associating our products with improved patient outcomes. About the Role Bayesian ships FDA-cleared, AI clinical decision support software directly into Epic and Oracle Health workflows at health systems across the country. Every release, every model update, and every clinician report that an alert didn't behave as expected runs through a quality and regulatory system that has to be as rigorous as the software itself. You will help drive that system. This role intentionally wears multiple hats. We're a small company, and we need one person who can do several things well: engineer quality into the software as it's built, handle the post-market side once it's in production, and keep the quality management system and our regulatory obligations current as we scale. You'll work directly with engineering, data science, clinical, and implementation teams, with support from company leadership, while under the direction of the Head of Quality and Regulatory. You're the engineer in the room on quality questions. When a hospital reports that the model flagged a patient late, you decide whether it's a complaint, whether it's reportable, and what changed in the software or the data. You can read the code, the logs, and the test evidence to find out. What You'll Own Software Design Quality Partner with engineering and data science through the full software lifecycle: requirements, architecture review, software risk analysis, verification and validation, traceability, and release readiness in accordance with IEC 62304, ISO 14971, and 21 CFR 820 (QMSR) design controls. Keep the design history file and risk management file current, right-sized, and defensible. Change Control & Algorithm Lifecycle Assess software and model changes for regulatory impact, determining whether a letter-to-file or a new submission applies, and drive the change through the quality management system. Maintain the risk file and support post-market performance monitoring of the deployed algorithm. Complaint Handling & Post-Market Surveillance Support complaint intake, triage, investigation, and closure. Prepare MDR reportability assessments under 21 CFR 803 for review and approval, trend complaints and field data, and lead nonconformance reports and CAPAs when patterns emerge. Work closely with the implementation and clinical teams, who hear from clients first, to make sure feedback reaches the quality system. QMS Improvement & Maintenance Maintain and update quality procedures, document control, training records, and compliance evidence as the company grows. Support internal audits, prepare management review inputs, and manage supplier controls for EHR, cloud, and subcontractor relationships. Regulatory Interactions & Submissions Contribute to 510(k)s, Q-Submissions, and Predetermined Change Control Plans. Respond to FDA questions and support the team during FDA inspections. Regulatory Intelligence Monitor FDA guidance on AI/ML-enabled devices, cybersecurity under Section 524B, and quality system expectations. Translate emerging requirements into concrete changes to procedures and product requirements. Cross-Functional Collaboration Embed compliance into how product, engineering, and commercial teams already work, so that quality speeds delivery rather than slowing it down. Communicate quality metrics and risk clearly to technical and non-technical audiences, including executives. What You'll Bring A BS in Computer Science, Systems Engineering, Biomedical Engineering, or a related technical field, or equivalent practical experience 5+ years in software quality, design quality engineering, or regulatory work for software medical devices under ISO 13485 and IEC 62304, including hands-on ownership of design controls and ISO 14971 risk managem

Enterprise Growth Lead 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. We are looking for an experienced, motivated Enterprise Growth Lead to lead revenue growth in a territory. In this role, you will develop and execute a sales and account growth strategy to drive adoption of our solutions across health systems. You’ll be at the forefront of our mission, working closely with hospital executives and clinical leaders to bring our groundbreaking technology to life. Who We Are We’re using state-of-the-art tech to build AI co-pilots for doctors and nurses to literally help them save lives! Read more about our recent publication in Nature Medicine that associates our products with lives saved. We’re a diverse and experienced team of AI/ML experts, software engineers, product designers, behavior change specialists, and clinicians. We’re not afraid of hard problems and are highly results-oriented. We also like to have fun while we’re working on hard things. Our culture is highly collaborative, inclusive, supportive, and we have a strict “no jerks” policy. 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. Who You Are Proven Commercial Leadership: 7+ years of sales and account management experience with a strong track record in healthcare and/or SaaS sales, specifically within hospital systems and early stage, innovative concepts to C-suite buyers. Healthcare consulting and financial services success will also be considered. Exceptional Communication and Negotiation Skills: Ability to effectively communicate the value proposition and challenge diverse stakeholders in order to win complex, high-stakes deals. Data-Driven Decision Making: Skilled in sales analytics, and pipeline forecasting Team Leadership Experience: Proven experience in leading, coaching, and motivating teams to achieve ambitious targets. Adaptability: Thrive in a start-up environment with a strong ability to pivot and adapt as the company scales. What You’ll Do Sales Strategy and Execution: Develop and implement a strategic sales and account growth plan for the region to exceed revenue goals and drive long-term growth. Relationship Management: Build and nurture strong relationships with C-level executives, key stakeholders, and decision-makers within hospital systems. Team Leadership and Development: Lead, mentor, and develop a high-performing team; provide guidance on complex negotiations, consultative selling, and professional growth. Market Insights: Stay current with industry trends, market conditions, and competitor offerings to refine the go-to-market approach and position our technology effectively. Collaborative Execution: Partner with Leadership, Product / Tech and Customer Success teams to ensure alignment on messaging, product feedback, and post-sale support. Preferred Qualifications Bachelor’s degree in Business, Marketing, Healthcare Administration, or related field; MBA, MHA or MD / DO is a plus. Experience with hospital-specific technology solutions, including those with EMR integration Network of contacts within hospital systems and healthcare networks. 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.

Clinical Integration – Nurse Consultant In Brief We’re a rapidly growing startup on a mission to make healthcare proactive by empowering clinicians with real-time data to save lives. We’re looking for a full-time nurse consultant with 5+ years of clinical experience as a registered nurse with a strong understanding of healthcare processes and workflows; demonstrated leadership skills and involvement with quality improvement and/or experience in clinical informatics/analytics roles. Who We Are We’re using state-of-the-art tech to build AI co-pilots for doctors and nurses to literally help them save lives! Read more about our recent publication in Nature Medicine that associates our products with lives saved. We’re a diverse and experienced team of AI/ML experts, software engineers, product designers, behavior change specialists, and clinicians. We’re not afraid of hard problems and are highly results-oriented. We also like to have fun while we’re working on hard things. Our culture is highly collaborative, inclusive, supportive, and we have a strict “no jerks” policy. 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. What You’ll Do This role is critical to our ability to accelerate and scale our clinical AI product deployment as we expand our client base. You will: Collaborate closely with clients to ensure successful integration of our solutions, providing exceptional support and guidance. Conduct comprehensive chart reviews to identify opportunities for model refinement, potential enhancements to the product, and to gather success stories. Build and nurture strong relationships with clinicians at client sites to facilitate seamless adoption and utilization of our technology. Provide leadership and guidance to internal teams on clinical matters, leveraging your expertise to drive success. Contribute to the development of presentations and participate in sales and marketing conversations, representing the nurse perspective, and demo product features. Stay abreast of industry trends and advancements, contributing to the continuous improvement of our products and services. Gain buy-in from nursing and physician stakeholders to drive adoption. Support cross-functional team to build and deliver overarching narrative regarding value that Bayesian brings to each health system customer. Support research and evaluation of Bayesian Health modules. Identify gaps and barriers to achieving clinical outcomes and recommend countermeasures. Contribute to the product roadmap by anticipating client needs. Travel an average of 10% (including overnight) to client sites to provide support. Be an integral part of our diverse, inclusive, collaborative, fully-remote Clinical team. Other duties as assigned. Who You Are Clinical experience as a registered nurse, with a strong understanding of healthcare processes and workflows. Demonstrated leadership skills, with the ability to inspire and motivate teams towards common goals. Previous involvement with quality improvement teams (e.g. sepsis or HAPI) or experience in clinical informatics/analytics roles is highly desirable. Excellent communication skills, both written and verbal, with the ability to effectively convey complex information to diverse audiences ranging from frontline clinicians to healthcare executives. Flexibility and adaptability in a fast-changing environment, with the ability to thrive in a dynamic start-up culture. Self-motivated and proactive, with a passion for driving innovation and improving healthcare outcomes. You are passionate about making clinical care more effective and efficient. You believe technology has the power to inform clinical decisions early, and you want to make that a reality. You have an executive presence and grit. You’re comfortable leading executive and frontline teams, and you’re able to articulate complex technology to audiences of varying backgrounds. You’re results oriented. Everything you do contributes to achieving a specific outcome, and you have a track record of exceeding expectations. Continuous improvement is in your DNA. You question the status quo and look for ways to drive efficiencies internally and externally. You have a track record as a collaborative, driven team player with a high sense of ownership. Nice to Haves Demonstrated problem solving through research or projects Ability to understand and interpret clinical research 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 expr

Staff Machine Learning Engineer 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. 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. Read more about our recent publication in Nature Medicine that associates our products with lives saved. What You’ll Do 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.