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Lotus AI

AI-driven feature automation from feedback

Research Engineer

AI ResearchConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USANo salary listedIn-person

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

AI-driven feature automation from feedback

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
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
2026

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