Knowledge Routing Engineer
About the job
- At least 7 years of machine learning engineering experience.
- Experience working with foundational machine learning models, such as learned decision trees, deep learning, and reinforcement learning.
- Strong backend engineering skills and systems thinking.
- Experience working with ambiguous problems and defining solutions from first principles.
- Experience turning research or novel techniques into testable prototypes.
- Build and own the core symptom and query routing engine.
- Build models that map complex queries and symptoms to urgency classifiers, providers, and specialties.
- Build learned decision trees that infer whether follow-up questions are needed to gain more insight into a patient's specific query.
- Leverage insights and learning from real protocols, such as Schmidt-Thompson, and other triaging standard operating procedures.
- Work with medical professionals to build generalizable representations of how queries and symptoms map to body systems, specializations, and restrictions.
- Build self-learning models that learn and iterate from real user data and diagnoses.
- Establish quality metrics and iteratively improve the model over the long term.
- Experience with evaluation frameworks and model quality measurement.
- Experience with medical artificial intelligence systems.
- Experience designing human-in-the-loop workflows for machine learning.
- Built self-learning decision trees to solve complex problems.
- Researched and implemented foundational machine learning models.
- Built self-learning neural network architectures to solve real-world problems.
- Leveraged reinforcement learning and Markov decision processes to learn optimal policies for online systems.
About the company
Sage Care provides a digital health platform that serves as a care navigation system for health systems. It uses clinically intelligent AI agents and optimization algorithms to automate 24/7 patient triage, appointment scheduling, referral processing, and follow-up coordination for diagnostics and care plans. The platform is designed for rapid deployment—its AI agents can be trained and running within 48 hours—and targets health systems, multispecialty clinics, and large providers. Sage Care aims to boost provider revenue by 15-20% through better care coordination, fewer no-shows, and more efficient patient flow.
Company Size
11-50
Company Stage
Early VC
Total Funding
$20M
Headquarters
Palo Alto, California
Founded
2015
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Simplify's Take
What believers are saying
- Sage launched October 17, 2025 with $20 million from Yosemite and General Catalyst.
- Jiva Health, Bronson Healthcare, and White Plains Hospital provide real enterprise validation.
- Forbes reported $5 million 2026 revenue expectations, signaling early commercial traction.
What critics are saying
- Epic and major EHR vendors already own scheduling and referral workflows.
- CMS prior-authorization API mandates starting January 1, 2027 commoditize parts of Sage's value.
- If Bronson or White Plains pilots stall, Sage becomes another underpenetrated workflow startup.
What makes Sage Care unique
- Justin Ho, Caesar Djavaherian, and Chris Blumenberg combine logistics, clinical, and systems expertise.
- Sage Care orchestrates calls, triage, scheduling, referrals, and follow-ups across health systems.
- The platform claims 48-hour deployment and health-system workflow integration, not generic chat support.
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Benefits
- Hybrid Work Options