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Lotus AI

AI-driven feature automation from feedback

Research Engineer

Full-Time
No salary listed
Mid
San Francisco, CA, USA
In Person
AI & Machine LearningAI Research

About the job

Requirements
  • Strong Python skills and deep experience with PyTorch or JAX.
  • A track record of shipping applied machine learning or large language model features to real users, beyond prototypes.
  • Hands-on experience with retrieval-augmented generation, prompt and tool design, evaluation harnesses, and error analysis.
  • Solid Structured Query Language skills and familiarity 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.
Responsibilities
  • Build and iterate on agentic workflows using 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.
  • Curate high-quality datasets from electronic health records, claims, laboratory data, devices, and chat logs with rigorous deidentification.
  • Design synthetic data and clinician-in-the-loop labeling pipelines that reflect real clinical use.
  • Own the evaluation stack for medical correctness, hallucination, bias, safety, latency, and cost.
  • Build automated red-teaming and regression suites tied to clinical guidelines and source citations.
  • Ship research to production with robust observability, feature flags, and rollback plans.
  • Optimize inference with batching, quantization, Low-Rank Adaptation or Quantized Low-Rank Adaptation, and vLLM or TensorRT where appropriate.
  • Collaborate with data and product engineers on retrieval, storage schemas, and lineage so every claim is explainable.
Desired Qualifications
  • Experience with clinical ontologies and standards such as SNOMED CT, ICD, LOINC, RxNorm, Fast Healthcare Interoperability Resources, and NCPDP.
  • Background in Reinforcement Learning from Human Feedback or Reinforcement Learning from AI Feedback, 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 evaluation frameworks.
  • Deep familiarity with observability stacks such as Sentry and Langfuse and containerized deployments such as Docker or Elastic Container Service.

About the company

Lotus AI builds an AI-powered platform for product teams that turns customer feedback into ready-to-use features. It centralizes and analyzes user input, removing manual data work, and uses AI to translate insights and requests directly into development tasks. This lets teams skip guesswork and prioritize features that actually impact user retention, moving faster with a roadmap aligned to real user needs. Compared with traditional product-management tools, Lotus AI automates the end-to-end flow from feedback to deployable feature, enabling faster delivery and more confident decisions. The company aims to help teams achieve higher product velocity and market relevance by focusing development on high-impact work.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

2026

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Simplify's Take

What believers are saying

  • Lotus raised $41M on January 24, 2026, from top healthcare investors.
  • Its May 12, 2026 study showed 98% clinician approval of finalized AI actions.
  • The company now claims 24/7 primary care, broad labs, and nationwide prescriptions.

What critics are saying

  • Lotus Health AI reported only $550K revenue and five employees in 2026.
  • Telemedicine rivals like Citizen Health and MyAria target the same virtual-care wedge.
  • Physician-liability and prescribing scrutiny can shut down the model quickly.

What makes Lotus AI unique

  • Lotus Health AI pairs AI triage with licensed physicians and prescriptions.
  • Its asynchronous workflow precomputes care actions, then clinicians approve them.
  • It reaches 6,000+ lab sites and any U.S. pharmacy.

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Benefits

  • Company Equity