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Assort Health is building AI agents that create continuous conversations for patients throughout their healthcare journey. The company has grown from 15 people in 2025 to 250+ by end of 2026, with 20x revenue growth in 15 months and $222M raised (including $120M Series C at $1.2B valuation). They've built the largest proprietary specialty dataset in healthcare: 270M patient interactions, 62K care protocols, and 1.6M decision pathways.
As a Research Engineer, you will own large initiatives that push the boundary of what AI models and agents can accomplish in healthcare while maintaining high reliability, efficiency, and precision. You'll work end-to-end from research idea to production, making high-impact technical decisions.
Key responsibilities:
- Lead research and engineering efforts to improve core conversational capabilities in production, including instruction following, tool calling, retrieval, and memory
- Investigate research questions in speech and audio; design experiments to test hypotheses about model behavior and capabilities
- Build and iterate on end-to-end models and pipelines optimizing for quality, efficiency, and user experience
- Identify opportunities for model-task optimization to ensure right model architectures for different tasks based on performance, latency, and cost
- Partner with platform and product engineers to integrate new models into production systems
- Break down ambiguous research ideas into clear, iterative milestones and roadmaps
- Train, fine-tune, validate, and develop models built in-house and by customers
- Design evaluation protocols and benchmarks measuring model quality, generalization, robustness, and progress against research objectives
- Analyze datasets, model outputs, and failure cases to guide next rounds of model development
Requirements:
- 5+ years of experience with minimum 3+ years in AI/ML engineering or research
- Prior experience post-training and deploying LLMs in production environments
- Fluency in Python and modern ML tooling (training, evaluation, inference, data pipelines)
- Track record of taking research ideas from prototype to reliable, measurable production impact
- Strong experimental judgment: formulating hypotheses, establishing useful baselines, designing evaluations, and interpreting results carefully
- Bonus: Prior experience with speech-to-text (STT), text-to-speech (TTS) models, and/or duplex models
- PhD not required; demonstrated research ability and quality of models, experiments, and systems valued
