Pelica Health is a Y Combinator backed AI company building the operating system for value-based care. We unify claims, EHR, pharmacy, lab, and ADT data into one live record per member, then put an AI copilot next to every team that depends on it: risk adjustment, Quality and Stars, pharmacy and Part D, provider network, and care management.

Founded by former engineering and AI leaders from Google and YouTube. Backed by Y Combinator. 175,000+ patients managed live on Pelica today.

Read our founder letter first: https://www.pelica.com/blog/why-we-started-pelica

Full careers page (with the apply form): https://www.pelica.com/careers

What you will do

- Build and own production machine learning systems end to end: data modeling, feature engineering, training, evaluation, deployment, and monitoring.

- Design and implement data pipelines that turn raw, messy real-world healthcare data (claims, EHR, pharmacy, lab, ADT) into reliable features.

- Train and evaluate models for ranking, prioritization, and prediction, for example identifying high-risk or high-priority members.

- Deploy models as reliable services or batch jobs, with clear versioning, monitoring, and rollback strategies.

- Make architectural decisions around model choice, evaluation metrics, retraining cadence, and system guardrails. Balance accuracy, explainability, reliability, and operational constraints.

- Collaborate directly with founders and engineers to translate product and operational needs into scalable, maintainable ML solutions.

What we are looking for

- At least 3 years building and deploying machine learning systems in production.

- Strong foundation in ML for structured (tabular) data: feature engineering, regression or classification models, ranking or prioritization.

- Experience with the full ML lifecycle: data prep, train/test, evaluation, deployment, retraining, monitoring.

- Solid backend engineering skills: production-quality code, services or batch jobs, databases, data pipelines.

- Good system design instincts. You understand trade-offs between model complexity, reliability, latency, and maintainability.

- Ability to clearly explain modeling choices, assumptions, and limitations to non-ML stakeholders.

- Bonus: healthcare or operational decision-support systems; LLMs in production (RAG, fine-tuning, structured prompting); model monitoring and data drift tooling.

Why join

- Work on real problems. 175,000+ patients are managed live on Pelica today. Teams using our copilots are closing care gaps and saving real time.

- Learn from senior operators. Co-founders built and led large teams at Google and YouTube. You will get unusual exposure to system design, scale, and ML at production grade, on a team small enough that you own real surface area.

- Speed and ownership. Five people, no committees. You will ship models end to end, work directly with founders, and see your model output in front of real users within days.

Further reading

- Why we started Pelica Health: https://www.pelica.com/blog/why-we-started-pelica

- AI Agents vs Analytics Dashboards in Value-Based Care: https://www.pelica.com/blog/ai-agents-vs-analytics-dashboards

- What an AI Agent Does to Close a Care Gap: https://www.pelica.com/blog/anatomy-of-ai-care-gap-closure

- Replace the BI Ticket Queue With AI Questions (Lalit, CTO): https://www.pelica.com/blog/replace-bi-ticket-queue-ai

- Glossary of value-based care terms (HCC, V28, RAF, MAO-004, ADT): https://www.pelica.com/glossary

How to apply

One short form at https://www.pelica.com/careers (name, email, role, resume link). We read every submission within 5 business days and reply directly from a real founder email.

Job Type: Contract or Full-time

Pay: $80,000 to $150,000 per year

Location: San Francisco, CA or fully remote (US only)

Visa sponsorship: available

Work authorization: US citizenship/visa not required

Apply at: https://www.pelica.com/careers

Pay: $80,000.00 - $150,000.00 per year

Benefits:

1. Health insurance
2. Vision insurance

Work Location: Remote

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