Build and improve pipelines that parse clinical documents into validated, executable modules.
Run experiments across open and closed models, fine-tuning, and constrained decoding methods.
Work with clinicians to evaluate outputs and turn model failures into system improvements.
They build a compiler that converts clinical standards into verified, traceable decision logic for patient care. This healthtech team combines frontier model research with production engineering to improve clinical decision support.
Build production pipelines that parse clinical standards into executable modules using document and layout models.
Run structured experiments comparing open and closed models, fine-tuning, and constrained decoding for guideline logic.
Create deterministic validators and benchmarks to surface ambiguity, contradictions, and missing evidence in clinical outputs.
They build a production compiler that turns clinical standards into verified, traceable decision artifacts for healthcare. The team is research-focused and collaborative, with clinicians and technical leadership working closely; company size is not disclosed.
Build a pipeline for parsing clinical documents and validating executable modules.
Design and refine a target syntax for representing guideline logic.
Run experiments across open and closed models, fine-tuning approaches, and constrained decoding.
They build a compiler that turns clinical guidelines into structured, executable decision logic for healthcare. The team is research-focused with production engineering stakes, working closely with clinicians and technical leadership.
Build production pipelines that parse clinical standards into validated, executable modules.
Design and refine representations for guideline logic, including exclusions, precedence, and recommendations.
Evaluate models, develop benchmarks and adversarial cases, and ship successful improvements into production.
This healthtech company builds a production compiler that turns clinical standards into executable, traceable decision logic. The team is research-focused and collaborative, working across disciplines to improve the reliability of clinical decision systems.
Build pipelines that parse clinical standards and transform them into executable modules using document and layout models.
Evaluate open and closed models, fine-tuning approaches, and constrained decoding strategies.
Develop datasets, benchmarks, metrics, and adversarial cases to assess clinical fidelity and correctness.
They build a clinical AI compiler that turns healthcare standards into validated, executable decision logic. The team is research-focused, collaborative, and works closely with clinicians to make recommendations traceable and reliable.
Build and improve pipelines to parse clinical documents into validated executable modules.
Design and refine target representations for clinical guideline logic.
Develop deterministic validators using static analysis to make ambiguity explicit.
This healthtech team is building a production compiler that converts clinical standards into structured, executable decision logic. The team size is not specified, but the role emphasizes collaboration with clinicians and technical colleagues.
Own, debug, and improve production ML pipelines for accuracy and efficiency.
Design LLM evals, LLM-as-a-judge systems, datasets, and benchmarks to monitor quality.
Run experiments on prompts, models, and pipeline designs to drive improvements into production.
Mimica is an AI-powered process intelligence platform that helps enterprises reclaim time by analyzing workflows and generating AI agents to automate tasks. Backed by $26M in Series B funding and trusted by Fortune 500 companies, the remote-first team spans 16+ countries and values high ownership and transparent communication.
Own the AI that assesses patients for US mental healthcare, from conversation to treatment recommendation.
Build evaluation harnesses and simulated patient conversations to test every configuration before deployment.
Raise the engineering bar through architecture, code review, and mentorship while ensuring regulatory compliance.
Limbic develops AI mental health chatbots for patient assessment and therapy, with clinical validation and FDA/NHS adoption. The company has supported over 820,000 patients and emphasizes safety, science, and an inclusive culture.
Run experiments that improve classification accuracy and ship winners to production.
Design and iterate on classifiers using prompting, retrieval, fine-tuning, and multi-model approaches.
Build evaluation sets and metrics; collaborate with clinical ops and legal teams.
Truemed enables health and wellness merchants to accept HSA/FSA funds by determining product eligibility for pretax spending. We are a Series A startup supporting brands like Peloton, focused on helping people invest in healthy habits.
Design multi-step LLM systems for reasoning, retrieval, planning, and tool use.
Own evaluation from offline benchmarks to online experiments and model-graded review.
Set quality, latency, and cost targets, and mentor senior engineers.
They build enterprise AI systems, specifically agent systems for large customers. As a late-stage, venture-backed company, they focus on shipping reliable AI to enterprise clients.
Build repeatable benchmarks and evaluation pipelines for model accuracy, hallucinations, retrieval quality, latency, and cost.
Turn research prototypes into production retrieval, drafting, document, and agent workflows.
Develop backend services, APIs, and internal tools to support testing and releases.
They are a healthtech company building dependable AI products for legal work. Their team is product-focused and works remotely across the United States.
Design, deploy, and optimize large-scale ML systems for retrieval, ranking, and LLM-powered features.
Lead ML projects from concept to production, improving answer relevance and user experience.
Collaborate with Product, Data Science, and Engineering teams to shape technical direction.
The hiring partner is a technology company focused on building advanced AI systems that help users discover relevant answers from large collections of online conversations. It values innovation, collaboration, and responsible AI development, offering a remote work environment within the United States.
Own the design and delivery of data engineering and clinical NLP pipelines that transform structured and unstructured EMR data into standardized clinical data.
Develop hybrid approaches using rules, dictionaries, deep learning, and LLMs for clinical entity extraction, normalization, and context interpretation.
Partner with clinicians to define schemas, validate OMOP CDM mappings, and ensure production reliability for transplant-focused data.
CareDx is a precision medicine diagnostics company advancing care in transplant, specialty oncology, and cell therapy through molecular diagnostics, digital health solutions, and AI-powered analytics. The company fosters a collaborative culture where every employee contributes to innovations that transform patient care.
Fine-tune open-weight LLMs using SFT, LoRA/QLoRA, and post-training methods such as DPO and GRPO to shape model behavior for 50M+ users.
Diagnose model failures and turn them into experiments, building training data and evals that directly influence production models.
Ship to production, speed up the training loop, and collaborate with Product, Web, and DevOps teams.
EverAI is building the world's largest AI companionship platform, redefining relationships for millions. With ~100 people, it's a fully remote, hardworking team with an ownership-driven culture and a track record of scaling products from 0 to IPO.
Build, train, and evaluate machine learning models end to end, from data and experiment design through training and reporting.
Design reinforcement learning environments, reward functions, and verifiers, and fine-tune language models using methods like PPO, DPO, and GRPO.
Collaborate with domain experts, analyze datasets, and present findings clearly to both technical and non-technical audiences.
EnableComp provides specialty revenue cycle management solutions for healthcare organizations using its unified E360 RCM platform. It is a multi-year Top Workplaces recipient and has been named to the Inc. 5000 list of fastest-growing private companies for eleven years.
Lead end-to-end delivery of complex healthcare AI products, including agentic workflows, RAG systems, and production services.
Collaborate with Product, Engineering, Data, and clinical teams to translate stakeholder needs into validated, access-aware AI workflows.
Own evaluation frameworks, model optimization, and human-review controls to keep high-stakes workflows safe, reliable, and governable.
NeueHealth is a value-driven healthcare company that aligns the interests of health consumers, providers, and payors to make healthcare accessible and affordable. They deliver clinical care through owned clinics and provider partnerships while enabling performance-based care with technology and services.