Research Engineer
$190k - $240k • San Francisco • FullTime
Posted 24d ago
Job Location
San Francisco
Tech Stack
Remote Work Policy
On-site
Employment Type
FullTime
Categories
AI Research Engineer
About the job
Assort Health is building a continuous conversation for every patient, powered by an AI agent that remembers context and carries it through their healthcare journey. The company has developed a proprietary dataset of 285 million patient interactions and is experiencing rapid growth, having raised $222 million. As a Research Engineer, you will be responsible for developing industry-leading healthcare AI models and pipelines, taking them from concept to production. You will own significant initiatives to advance the capabilities of AI models and agents in healthcare, ensuring high levels of reliability, efficiency, and precision.
Responsibilities
- Lead research and engineering to enhance core conversational AI capabilities in production, including instruction following, tool calling, retrieval, and memory.
- Investigate research questions in speech and audio, and design experiments to test hypotheses about model behavior and capabilities.
- Build and iterate on end-to-end models and pipelines optimized for quality, efficiency, and user experience.
- Identify opportunities for model-task optimization, selecting appropriate model architectures 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 further develop in-house and customer-developed models.
- Design evaluation protocols and benchmarks to measure model quality, generalization, robustness, and progress against research objectives.
- Analyze datasets, model outputs, and failure cases to guide the next round of model development.
Requirements
- 5+ years of experience, with a minimum of 3+ 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.
- Experience utilizing and improving speech-to-text (STT), text-to-speech (TTS) models, and/or duplex models is a bonus.
Benefits
- Competitive compensation including salary and employee stock options.
- Annual budget for professional development and training opportunities.
- Office setup stipend.
- Top-tier health coverage (medical, dental, vision).
- Flexible PTO.
- Provided meals and snacks.
- Fitness stipend.
- Commuter benefits.
- 401(k) plan.