Research Engineer

Assort Health

. Build industry-leading healthcare AI models and model pipelines powering voice agents and the patient platform .

Posted 9/24/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $190,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and optimizing AI models and pipelines for healthcare applications, with a strong focus on conversational capabilities and model performance. Proven ability to lead research initiatives and integrate models into production systems while ensuring reliability and efficiency.

Highest-signal resume keywords

AI/ML EngineeringPython ProgrammingModel DeploymentExperimental DesignSpeech Recognition

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI Model DevelopmentMachine LearningData AnalysisModel EvaluationModel Fine-TuningPipeline OptimizationHypothesis TestingPerformance OptimizationConversational AIEnd-to-End Model Building

Soft Skills

Strong Experimental JudgmentCollaborationProblem Solving

Tools & Technologies

ML ToolingData PipelinesProduction Systems

Industry Keywords

Healthcare AIVoice AgentsSpeech-to-TextText-to-SpeechConversational Capabilities

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Build industry-leading healthcare AI models and model pipelines powering voice agents and the patient platform
Own large initiatives advancing model and agent capabilities in healthcare while maintaining reliability, efficiency, and precision
Lead research and engineering to improve conversational capabilities, including instruction following, tool calling, retrieval, and memory
Investigate speech and audio research questions and design experiments to test model hypotheses
Build and iterate end-to-end models and pipelines optimized for quality, efficiency, and user experience
Identify model-task optimization opportunities based on performance, latency, and cost
Partner with platform and product engineers to integrate new models into production systems
Convert ambiguous research ideas into iterative milestones and roadmaps
Train, fine-tune, validate, and further develop in-house and customer-developed models
Design evaluation protocols and benchmarks measuring quality, generalization, robustness, and research progress
Analyze datasets, model outputs, and failure cases to guide model development

Requirements

What you’ll need

5+ years of experience, with a minimum of 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, including training, evaluation, inference, and data pipelines
Track record of taking research ideas from prototype to reliable, measurable production impact
Strong experimental judgment, including hypothesis formulation, baseline establishment, evaluation design, and careful result interpretation
Bonus: prior experience utilizing and improving STT, TTS, and/or duplex models
A PhD is not required; demonstrated research ability and quality of models, experiments, and systems are valued
Ability to work in office 4 days a week
Visa sponsorship requirements must be disclosed

Benefits

Comp & perks

Employee stock options
Annual budget for professional development
Training opportunities
Office setup stipend
Medical, dental, and vision insurance
Flexible PTO
Lunch, dinner, and snacks
Fitness stipend
Commuter benefits
401(k)