Senior Software Engineer, Backend/ML

• We’re an early-stage startup that’s building a health AI platform to help clinicians make better use of real-time data to reduce preventable complications and save patient lives.

• We’re looking for a software engineer with breadth of experience across technical stacks who wants to make an impact in the healthcare space.

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.

This role is critical to our ability to expand and scale our platform and module offerings. Our platform and modules are 100% powered by data and ML, and it’s crucial to have a reliable platform to guarantee correctness of our application functionality.

You Will:

• Work closely with product managers, clinicians, data scientists, and other software engineers to build a highly reliable and scalable real time clinical AI platform.

• Collaborate with data scientists to accelerate our ML model development and deployment to production.

• Design, implement, and deploy health data pipelines and services that integrate with electronic health record (EHR) systems using FHIR and HL7 communication standards.

• Develop backend APIs and ML services to enable our clinical AI products.

• Partner with infrastructure engineers to design and deploy the infrastructure for our clinical AI platform on AWS.

Who You Are:

• You have 5+ years of experience in developing and deploying ML-based products and services in production.

• You have 5+ years of experience in building and maintaining highly scalable and reliable cloud-based production ML systems.

• You have 3+ years of experience using MLOps principles to build infrastructure that enables ML model development and deployment in production systems.

• You have 3+ years of experience with relational databases such as Postgresql, MySQL, etc.

• You have 3+ years of experience with cloud platforms such as AWS, Google Cloud, Azure, etc.

• You have hands-on experience implementing production ML systems at scale in Python, C++, or similar languages. Proficiency in Python is highly preferred.

• You have experience in solving complex system and storage challenges through scalable, fault-tolerant architecture.

• You get things done, you are comfortable with uncertainty, and you have the grit to overcome challenges and help our team build Bayesian Health for the long term.

• You have a track record as a collaborative, driven team player with a high sense of ownership.

• You have a BS in Computer Science or equivalent experience.

• Experience with health data, integration with electronic health records (EHR) systems, and Health IT interoperability standards is preferable.

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.