Senior Data Scientist, AI Retrieval Systems

Stack

Responsibilities

• ▹Model biomedical knowledge for rare disease research: ingest disease and phenotype ontologies and controlled vocabularies into PostgreSQL with a maintainable release and refresh path, reconcile identifiers across sources, and work through term hierarchies to determine what is clinically relevant
• ▹Build retrieval-augmented services that ground everyday language in clinical concepts: embed term labels, definitions and synonyms, retrieve candidates, and have a model disambiguate against context before any value is committed
• ▹Treat retrieval as a database problem: tune keyword and vector search over large biomedical corpora and defend the recall and latency trade-offs you choose
• ▹Build the ranking and relevance layers that decide what surfaces first, including domain-aware weighting and graceful degradation when a condition falls outside curated coverage
• ▹Deliver the interfaces where this work becomes visible to users in Next.js, React and TypeScript: question and confirmation flows, result presentation, live status for long-running pipelines
• ▹Deploy continuously onto NIH on-premises and high-performance computing Kubernetes environments: Helm charts, StatefulSets, secrets, ingress, GPU scheduling for self-hosted inference and scheduled jobs, in partnership with the operations teams
• ▹Build the evaluation that tells us whether retrieval and concept mapping are good enough to rely on, and keep it running as a regression suite
• ▹Log what the system does and why: request identifiers, latency, errors and the selected concept, so staff can review an AI-assisted result
• ▹Work out what researchers, clinicians and patient communities need and turn it into data models, retrieval behavior and interface design
• ▹Contribute to manuscripts, conference abstracts and posters with NIH investigators, credited as an author on work you helped produce

Requirements

• ▹Bachelor's degree in Data Science, Computer Science, Bioinformatics, Biomedical Informatics or a related field (advanced degree preferred; equivalent professional experience considered)
• ▹At least 5 years building and operating production software or data systems, including at least 2 years shipping LLM-powered applications (agents, retrieval or evaluation) that people depend on; depth in retrieval and applied LLM engineering is weighed more heavily than total years
• ▹Experience building retrieval systems end to end, covering indexing, query construction and measuring retrieval quality against real data
• ▹Experience evaluating systems that have no single right answer, using golden sets, offline regression suites or metrics such as Recall@K and MRR
• ▹Experience with structured output and tool or function calling: constraining a model to a typed schema and validating what came back
• ▹Ability to own a service end to end, from schema design through deployment and operation
• ▹Ability to obtain and maintain a Public Trust Security clearance
• ▹Python, with FastAPI, Pydantic and pytest
• ▹PostgreSQL at depth, covering vector search (pgvector or equivalent), full-text search, embedding pipelines, indexing and query tuning
• ▹LLM application engineering: provider APIs and gateways, prompt and context design, structured generation and tool use
• ▹Data ingestion and transformation pipelines with a repeatable refresh path
• ▹Containers and Kubernetes, enough to ship, debug and operate a service on infrastructure you do not administer
• ▹Working comfort in Next.js, React and TypeScript
• ▹Git-based collaboration and CI/CD in a shared codebase

Nice to have

• ▹Biomedical ontologies and controlled vocabularies (MONDO, HPO, UMLS, MeSH and other OBO Foundry resources), with comfort working through term hierarchies, synonyms and cross references
• ▹Grounding model output in a domain terminology through embedding-based retrieval plus model disambiguation, such as entity linking, concept normalization or ontology alignment
• ▹Helm and deployment to on-premises or HPC Kubernetes environments
• ▹Serving open-weight models in production with Ollama or vLLM behind a gateway such as LiteLLM, and work with domain embedding models such as MedCPT
• ▹Background in rare disease, clinical genetics or translational research
• ▹Contributions to an open biomedical resource, standard or consortium, such as OBO Foundry ontologies or GA4GH
• ▹Published or presented work that explains your engineering to people who did not build it (peer-reviewed papers, conference talks, preprints, technical blog posts, open source contributions)
• ▹Prior or current NIH experience

Soft skills

What we offer

• ▹100% medical, dental and vision coverage for employees
• ▹Paid time off and paid holidays
• ▹401K match up to 5%
• ▹Educational benefits for career growth
• ▹Employee referral bonus
• ▹Flexible spending accounts: healthcare (FSA), parking reimbursement (PRK), dependent care (DCAP) and transportation reimbursement (TRN)
• ▹Base salary of $130,000 to $150,000 depending on experience, qualifications, skills and location

About the company

Axle is a bioscience and information technology company offering translational research, biomedical informatics and data science solutions to research centers and healthcare organizations, including multiple institutes at the National Institutes of Health (NIH).