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 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 evaluations to measure and improve AI reasoning in complex, high-stakes decisions.
Collaborate with engineers, product, and domain experts to turn observed failures into testable improvements.
Own the quality of shipped systems, from code reviews to monitoring and integration.
Elicit builds AI systems that help research and business teams make evidence-based decisions on high-stakes questions. They are a remote-friendly, collaborative team that values rigorous thinking, experimentation, and in-person retreats.
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.
Build the component layer around our layout synthesis engine, including API contracts, services, and evaluation gates.
Turn model retraining into a one-command job with built-in benchmarks and readable results for the whole team.
Own latency and cost budgets for learned capabilities and partner with infrastructure engineers on MLOps and deployment.
Higharc is a VC-backed startup that is changing how new homes are designed and built using spatial AI and generative floor plan technology. The company is fully remote, has raised over $175M, and values flexibility, collaboration, and asynchronous deep work.
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.
Design and build challenging evaluations and executable environments for coding and long-horizon agents.
Develop scoring logic and verifiers to detect reward hacks and trace failures through model outputs and harness code.
Build and scale RL data pipelines for generating and curating challenging coding and agentic tasks.
Prime Intellect is building the open superintelligence stack, providing infrastructure for post-training frontier AI models and open-source models trained for long-horizon tasks. The company has raised $150M from top investors and is a mission-driven team passionate about accelerating science and AI.
Design and build automated evaluation pipelines for AI agents.
Develop testing frameworks for reasoning, multi-turn conversations, and adversarial scenarios.
Own the evaluation architecture and integrate observability tools in a fully remote team.
A company building production-grade AI agents and systems. They operate in a fully remote, globally distributed environment with a culture focused on innovation, autonomy, and continuous improvement.
Develop AI methods and algorithms for reliable agents.
Design simulations and evaluations for agent behavior.
Partner with product and engineering to ship research.
The company builds an AI agent platform focused on making agents reliable in production. It is a research-driven environment with a collaborative, startup-oriented culture.
Build and ship AI methods for federal research data with LLMs, NLP, RAG, knowledge graphs.
Benchmark AI against baselines and human reviewers to prove gains in accuracy, reliability, efficiency, cost.
Set standards for trustworthy AI and mentor data scientists through code review and guidance.
ARI builds AI methods for federal research-funding and administrative data, with clients including the NIH. It is a small multidisciplinary team of scientists, analysts, economists, and data scientists experienced with NIH data.
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.
Own the intelligence layer of Project Interstellar, building production LLM systems for document intelligence, voice agents, and task orchestration.
Design and maintain prompt engineering infrastructure, model abstraction, RAG layers, and agent orchestration frameworks.
Partner with engineering and domain experts to integrate AI capabilities into a HIPAA-regulated platform from the ground up.
Certum Legal Solutions is a legal managed services organization that provides operational infrastructure, technology, and back-office solutions for personal injury law firms. The company is building a proprietary AI-native system and is assembling a high-caliber team in a greenfield, fast-paced environment.
Implement embeddings, vector storage, and retrieval across a large, provenance-tracked evidence base.
Integrate language models so generated text is bound to cited source records, and test for citation failures.
Own prompt and output-schema design, model packaging, versioning, serving, and rollback.
DEFCON AI is an insights company that leverages artificial intelligence, mathematical optimization, data analytics, and software engineering to build resilient optimization systems for complex operations. The company offers a fully remote, results-based environment with a focus on production systems and a strong benefits package.
Develop and improve AI methods, algorithms, and systems across the lifecycle of reliable AI agents.
Create new approaches for simulating, evaluating, and optimizing agent behavior in real-world settings.
Turn research ideas into working systems, prototypes, and production-facing capabilities.
The company builds infrastructure that helps enterprises make AI agents more reliable in production. It is a technical and research-focused team working on AI methods and practical systems.
Design and implement RAG pipelines and tool-calling architectures for conversational AI agents in healthcare.
Build production Python code using LangChain and modern LLM frameworks to solve novel healthcare AI problems.
Own end-to-end deployments, monitoring, and customer partnerships in production healthcare environments.
Hippocratic AI is building the first healthcare-only, safety-focused large language model to transform patient outcomes. The company is backed by leading healthcare and AI investors, with a team of physicians, hospital leaders, and AI pioneers from top institutions.
Building multi-agent systems and implementing agent-based workflows and AI automation solutions.
Developing and optimizing prompt engineering strategies, including evaluation and iteration.
Integrating LLMs and AI models into cloud-based applications and APIs while researching new AI tools.
Software Mind develops impactful software solutions for global companies, partnering with tech giants and unicorns on transformative projects. The company builds cross-functional engineering teams and embraces a culture of openness, respect, grit, and cooperation.