Full-Time

Research Engineer

Lotus AI

Lotus AI

1-10 employees

AI-driven feature automation from feedback

No salary listed

San Francisco, CA, USA

In Person

Category
AI & Machine Learning (1)
Required Skills
LLM
Sentry
Python
Software Testing
Model Distillation
PyTorch
SQL
Machine Learning
Docker
RAG
Electronic Health Records (EHR)
AWS
Observability

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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.

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 Jobs

Simplify's Take

What believers are saying

  • Lotus raised $35 million in February 2026, reaching $41 million total funding.
  • The product is free, removing insurance friction and accelerating consumer adoption.
  • Supporting prescriptions, specialist referrals, and multilingual access broadens usage beyond chatbots.

What critics are saying

  • OpenEvidence and other clinical AI rivals already synthesize evidence and patient history.
  • Lotus’s sponsored-content revenue model collides with trust, reimbursement, and medical ethics concerns.
  • If users distrust AI diagnoses or physician oversight fails, Lotus faces existential liability.

What makes Lotus AI unique

  • KJ Dhaliwal says Lotus offers 24/7 AI primary care in 50 languages.
  • Lotus combines physician review, medical evidence, and automated record syncing into one workflow.
  • Kleiner Perkins and CRV backed Lotus’s February 2026 raise, signaling strong investor conviction.

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