Research Engineer
At a glance
Mid-level AI Research role at Lotus Health AI. San Francisco · full-time · no salary stated · we estimate $200,000–$266,875.
Lotus Health AI has not published a salary for this role. The figure below is our estimate, not theirs.
aimlroles summary, based on the employer's posting.
What you'll do
- Build retrieval, tool-use and planning workflows that answer health questions with cited sources and clear uncertainty
- Fine-tune or distill models for medical-data summaries, extraction, classification and patient dialogue
- Create safety checks that route, defer or fall back when an answer may be unreliable
- Prepare deidentified clinical datasets and build synthetic-data and clinician-review labeling processes
- Test medical accuracy, hallucinations, bias, safety, speed and cost, then ship and monitor the systems in production
What you bring
- Strong Python skills and deep experience using PyTorch or JAX
- A record of putting applied machine-learning or LLM features in front of real users
- Practical experience with retrieval-augmented generation, tool and prompt design, evaluation and error analysis
- Solid SQL skills and familiarity with vector stores and retrieval methods
Who this fits
This founding research engineering role suits someone who can move between applied research and product engineering, and turn complex systems into dependable components. You'll work on-site in San Francisco alongside clinicians and the founding team, with responsibility for setting research direction and shaping model and agent architecture.
From the employer
Research Engineer
About Us
Lotus Health 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.