Doctronic
Senior AI Engineer
New York City · Senior · Full-time
Sponsorship not specifiedDetected 4 days ago
AlgorithmsMachine LearningData ScienceLLMsRAGMLOpsA/B TestingComplianceHIPAAHL7/FHIREHR/EMRResearch
About the role
- Doctronic runs a real clinical practice, with patients consulting our AI doctor every day.
- That gives us a dataset no one else has to test ideas against.
- We're committed to publishing and open sourcing as we go.
Responsibilities
- Design and implement the next generation of the architecture behind Doctronic's AI doctor, including reasoning, reflection, verification, tool use, routing, uncertainty handling, and escalation.
- Build systems in which specialized agents and models work together to make clinical decisions safely, reliably, and efficiently, with an architecture that supports self-improvement over time.
- Build the evaluation platform, rubrics, simulations, and experiments that measure how the AI doctor performs and know when a benchmark score rewards the wrong behavior.
- Build the training data, feedback, reward, and experimentation pipelines that turn evaluation results and clinical expertise into system improvements.
- Wherever you're working, you'll own the problem end-to-end, from framing it to measuring whether it worked.
- Autonomy here means moving fast on your own judgment and bringing in clinical, product, or engineering partners early when the problem calls for it, not after.
- Doctronic is backed by Union Square Ventures, Lightspeed Venture Partners, and Abstract Ventures, with three rounds of financing completed between February 2025 and January 2026.
- You are a research-minded engineer who wants to build intelligent systems and is equally serious about understanding and demonstrating their effectiveness.
- Model evaluation, experimentation, and rubric design
- You have strong engineering fundamentals, you build real systems, not just notebooks or one-off experiments.
Requirements
- You have deep experience in at least two of the following:
- You have strong ML fundamentals, including training data, objectives, metrics, failure analysis, calibration, and validation.
- Typically, candidates will have an advanced degree in a quantitative, computational, or scientific discipline and 3+ years of highly relevant applied or research experience in AI/ML
- Experience with human-feedback systems, RLHF, simulation, or synthetic-data generation
Compensation
- Competitive salary plus meaningful equity with real upside as we grow.
Benefits
- Competitive salary plus meaningful equity with real upside as we grow.
- Build AI systems transforming healthcare for millions
- Comprehensive health benefits
- Model training, fine-tuning, distillation, or reinforcement learning
- Apply methods such as fine-tuning, distillation, reinforcement learning, preference optimization, and prompt and system optimization to improve specific components of the AI doctor.
Equal opportunity
- equal opportunity employer.
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