---
title: 'Research Engineer at Lotus Health AI'
canonical: 'https://feeny.ai/job/research-engineer-lotus-health-ai-san-francisco-4ncdvg9sdw0x'
type: 'job'
last_seen: '2026-09-10'
---

# Research Engineer at Lotus Health AI

- **Company:** Lotus Health AI
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2025-11-24
- **Last confirmed live:** 2026-09-10
- **Apply:** https://jobs.ashbyhq.com/lotushealth/89b6a814-2886-4a59-be60-61ba4d7fd1e9

## Job description

Research Engineer

## About Us

[Lotus Health](https://lotushealth.ai/) is a groundbreaking primary care app that integrates your medical records, AI, and real doctors to provide free, personalized healthcare and prescriptions. Our team includes ex-founders and engineers who have built and scaled consumer apps to millions of users, generating over $100M in annual revenue. Lotus is backed by Kleiner Perkins, and clinicians at Harvard and Stanford.

## Role Overview

We are hiring a Founding Research Engineer to design, prototype, and ship the core reasoning and agentic systems that power Lotus. You will turn messy health data into accurate, cited, and actionable guidance for patients and clinicians. The work blends applied research with product engineering: dataset curation, model training and evaluation, retrieval and tool use, safety and alignment, and putting breakthroughs into production. You will work side by side with clinicians and the founding team and your work will reach patients quickly.

## Responsibilities

- Research and Modeling
- Build and iterate on agentic workflows that use retrieval, function calling, and planning to answer health questions with citations and uncertainty awareness
- Fine tune and distill models for summarization, extraction, classification, and dialogue grounded in medical data
- Develop abstention, routing, and fallback strategies that favor safety and correctness
- Datasets and Labeling
- Curate high quality datasets from EHR, claims, labs, devices, and chat logs with rigorous deidentification
- Design synthetic data and clinician-in-the-loop labeling pipelines that reflect real clinical use
- Evaluation and Safety
- Own the eval stack for medical correctness, hallucination, bias, safety, latency, and cost
- Build automated red teaming and regression suites tied to clinical guidelines and source citations
- Systems and Production
- Ship research to production with robust observability, feature flags, and rollback plans
- Optimize inference with batching, quantization, LoRA or QLoRA, and vLLM or TensorRT where appropriate
- Collaborate with data and product engineers on retrieval, storage schemas, and lineage so every claim is explainable

What You Bring:

- Strong Python and deep experience with PyTorch or JAX
- Track record shipping applied ML or LLM features to real users, not just prototypes
- Hands-on experience with RAG, prompt and tool design, evaluation harnesses, and error analysis
- Solid SQL plus comfort with vector stores and retrieval patterns
- Product sense, pragmatism, and the ability to reduce complex systems into simple, reliable components
- Willingness to work on-site in San Francisco

Bonus Points:

- Experience with clinical ontologies and standards such as SNOMED CT, ICD, LOINC, RxNorm, FHIR, and NCPDP
- Background in RLHF or RLAIF, distillation, program-of-thought, and structured tool use
- Experience building speech or multimodal pipelines for medical settings
- Contributions to open source, published work, or well known eval frameworks
- Deep familiarity with observability stacks such as Sentry and Langfuse and containerized deployments such as Docker or ECS

Why Lotus: Join a team redefining how healthcare information is understood and acted upon. As a founding member you will set research direction, shape the model and agent architecture, and see your work improve care for real people at scale. You will work with exceptional engineers, clinicians, and researchers to build accessible, free primary care for everyone. If this sounds like you, we would love to meet.

## About Lotus Health AI

## Company Overview
- **One-liner**: Lotus Health AI is building the world's first AI-powered primary care copilot, unifying medical records, labs, wearables, and insurance into one secure app to deliver proactive, personalized care.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, USA
- **Founded**: 2024
- **Founders**: KJ Dhaliwal (CEO) and Zekka Nelson (CTO)

## Core Business
- **Primary industry**: Healthcare IT / AI-Powered Primary Care
- **Target customers**: B2C (patients seeking primary care), B2B (potential future employer-sponsored plans)
- **Mission**: To build the world's first AI-powered primary care copilot that unifies medical records, labs, wearables, and insurance into one secure app, combining cutting-edge AI with trusted clinicians to deliver proactive, personalized care.

## Products & Services
- **Lotus Health AI Platform**: A free, 24/7 AI-powered primary care service available in 50+ languages. The platform connects to medical records, wearables (Fitbit, Garmin, Oura, Dexcom, etc.), labs, and insurance. AI handles the majority of the diagnostic and treatment planning work, with board-certified physicians from top institutions (Stanford, Harvard, UCSF) reviewing and signing off on all final diagnoses, lab orders, and prescriptions. The service is licensed to operate in all 50 states and carries malpractice insurance.

## Market Standing
- **Valuation**: Not publicly disclosed
- **Total Funding**: $41 million (as of February 2026)
- **Latest Round**: $35 million Series A co-led by CRV and Kleiner Perkins (February 2026)
- **Notable Investors**: Kleiner Perkins, CRV, LEAD.VC (Adidas Family Office), plus founders and executives from Oura, Clover Health, Everly Health, Commure, and Forward
- **Key Metric**: Free service with no current revenue model; future models may include sponsored content or subscriptions. The company claims it can see 10x as many patients as a traditional practice.
- **Growth Signals**: Launched in May 2024; raised $41M total within ~2 years; operates in all 50 states; available in 50+ languages; backed by top-tier VCs; growing team of engineers, researchers, and clinicians.

## Competitive Advantages
- **AI-First Primary Care**: The platform handles the majority of diagnostic and treatment work via AI trained on millions of peer-reviewed studies and clinical guidelines, enabling 10x patient throughput compared to traditional practices.
- **Physician Oversight**: All AI-generated care plans are reviewed and signed off by board-certified physicians from top institutions (Stanford, Harvard, UCSF, Johns Hopkins), combining AI efficiency with human accountability.
- **Free Service**: The entire suite of care is currently offered completely free of charge, a key differentiator from competitors like Doctronic.
- **Data Integration**: Unifies medical records, labs, wearables, fitness/nutrition apps, genetic tests, and insurance into a single secure app with end-to-end encryption.
- **Regulatory Readiness**: Licensed to operate in all 50 states, HIPAA-compliant, and carries malpractice insurance.

## Strategic Focus
- **Product Development**: Current focus is entirely on product development and attracting patients rather than generating revenue.
- **Scale**: Building an AI system that can handle 10x the patient volume of a traditional primary care practice.
- **Clinical Validation**: Publishing research (e.g., "Physician agreement with AI-suggested care actions in asynchronous primary care" and "Making Medication Data Safe for AI Reasoning") to build clinical credibility.
- **Future Monetization**: Potential future business models may include sponsored content or subscriptions, but the company is currently prioritizing growth and product quality.

## Why Work Here
- **Mission-Driven**: Opportunity to "rebuild healthcare" from the ground up, working at the intersection of AI and clinical medicine.
- **Team Composition**: A mix of AI/ML engineers (from Yale, Johns Hopkins, Berkeley), senior iOS engineers (ex-Tinder), and clinical leaders (MDs from Stanford, Harvard, UCSF, UCLA).
- **Culture**: Described as building "the future of infinite care" with a focus on evidence-based, proactive medicine.
- **Work Environment**: Likely hybrid/office in San Francisco given the team concentration; specific remote policy not publicly detailed.
- **Funding & Stability**: Well-funded ($41M) with top-tier VC backing, providing strong runway for product development.
- **Impact**: Opportunity to work on a mission-driven product that directly addresses the U.S. primary care shortage and makes healthcare more accessible.

## Sources
1. [lotus.ai](https://lotus.ai/)
2. [lotus.ai/careers](https://lotus.ai/careers)
3. [lotus.ai/team](https://lotus.ai/team)
4. [techcrunch.com](https://techcrunch.com/2026/02/03/lotus-health-nabs-35m-for-ai-doctor-that-sees-patients-for-free/)
5. [lotus.ai/news/lotus-raised-41m](https://lotus.ai/news/lotus-raised-41m)

## Other roles at Lotus Health AI

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- [Communications Director](https://feeny.ai/job/communications-director-lotus-health-ai-new-york-tfqms512vw2m) — New York, NY
- [Community Director](https://feeny.ai/job/community-director-lotus-health-ai-new-york-yxgz0zdckcgj) — New York, NY
- [Growth Director](https://feeny.ai/job/growth-director-lotus-health-ai-new-york-kzvsy3gqt68y) — New York, NY
- [AI Content Lead](https://feeny.ai/job/ai-content-lead-lotus-health-ai-new-york-ydy8tf7e4q0y) — New York, NY
- [Art Director](https://feeny.ai/job/art-director-lotus-health-ai-new-york-brw4pqj8tby7) — New York, NY
- [Member of Technical Staff](https://feeny.ai/job/member-of-technical-staff-lotus-health-ai-san-francisco-meqztwqfdb0f) — San Francisco, CA
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