Athelas is a Sequoia funded biotech startup working on modern, point-of-care diagnostics using Machine Learning. Our main product is an FDA cleared device for immunoresponse monitoring. We're scaling deployments rapidly across the country, and our customer base includes major pharmaceutical companies. If you're interested in modernizing healthcare and working at the intersection of machine learning and healthcare, we are the right place for you.

Athelas is a small, creative, and hard-working team and we're looking for individuals with a founder-type mentality to join us.

About the Role

At Commure + Athelas, our Ambient AI team builds an AI Platform that turns real-time clinical conversations and clinical context into documentation and actionable insights for providers across the largest healthcare systems in the country. We’re looking for talented New Grad Software Engineers who love shipping quickly, obsess over user experience, and want to work on transforming healthcare.

This full-time position requires working 5 days a week in our Mountain View, CA office.

What You’ll Do

• Contribute to the most advanced ambient scribe platform used by clinicians nationwide
• Design and build end-to-end features, enhancing our existing systems to add new functionality.
• Architect and deliver full‑stack solutions emphasizing usability and security
• Maintain high standards for code quality, reliability, security, and performance
• Work with real-time audio capture, ASR, and LLM pipelines (prompting, structured outputs, post-processing)
• Collaborate across cross-functional product teams, working closely with product, design, ML and infrastructure to ship features to our customers.
• Be part of a tremendously fast-paced team that celebrates fast execution and clear decisions
• Work across the entire software stack with strong ownership and measurable outcomes

What You Have

• Solid CS fundamentals (data structures, networking, concurrency) and ability to debug across the stack
• Proficiency in at least one of: TypeScript/Node, Python, Go
• Product sense and empathy for clinicians; attention to detail on UX and correctness in high-impact workflows
• Excitement to work in a high-impact field with a builder attitude and bias for action

[Preferred]

• Exposure to LLMs (prompt orchestration, JSON-structured outputs, evals) or ASR/audio streaming
• Familiarity with modern frontend frameworks (e.g., React) or mobile frameworks (iOS/Android)
• Exposure to cloud and container technologies (e.g., AWS/GCP, Docker, Kubernetes) and CI/CD
• Experience (projects/internships) in ship-fast environments; comfort with CI/CD and feature flags
• General understanding of Containers and Cloud (Docker, Kubernetes; GCP/AWS)
• Security & compliance awareness (HIPAA/PHI, least-privilege, auditability), SSO/SCIM
• EMR/healthcare interfaces (HL7/FHIR) and external API design (idempotency, retries, pagination)

Experience areas we value (any subset):

• Building and operating production environments
• Alerting and reporting (PagerDuty, logging, tracing)
• Metrics tracking and dashboards (Grafana/Prometheus)
• Software Reliability Engineering concepts (circuit breakers, backoff, health checks)
• Strong communication, great product sense, and leadership potential; extremely motivated to grow

Machine Learning

Our device captures high resolution images of blood smears which we analyze using internally CNNs. Our networks are responsible for segmenting cells, classifying them, and deciding which images include valid and invalid samples. In addition, we have specially designed networks for classifying abnormal cells (blast cells, giant platelets, nucleated red blood cells) that require additional intervention.

Hardware

Our hardware stack includes custom objective lenses and image sensors to provide the optimal tradeoff for field of view and cell resolution. Our device includes an onboard linux processor, motor drivers, and a linear actuator for orienting and moving the sample. We are always looking to improve our imaging stack to provide more powerful images for analysis.

Clinic Product

We provide customers (clinics) a web-based interface for analyzing results, looking up patient history, and integrating directly with pharmacies. Our frontend is built entirely in react and redux.

Server API

Our APIs are built using flask and sqlalchemy with a postgres database. Our infrastructure is hosted using Kubernetes on GCP. We believe in simple, reliable infrastructure that allows us to spend most of our time on improving our tests and adding new ones.