Remote Senior Data Scientist, AI Retrieval Systems

Axle; United States; Remote; USD 130,000 - 150,000; Full time

Benefits offered by this job

Paid Time Off and Holidays

401K match up to 5%

Educational Benefits for Career Growth

Employee Referral Bonus

Flexible Spending Accounts: Healthcare

Job summary

Axle, a bioscience and information technology company, seeks a Senior Data Scientist, AI Retrieval Systems to support NIH rare-disease research. This remote, US-based role owns the data layer, retrieval services, interfaces, and deployment on NIH on-prem HPC Kubernetes environments.

You will build ontologies, semantic search, and ranking for clinical concepts, collaborating with NIH program staff and clinical geneticists. Strong LLM, retrieval, and biomedical vocabularies experience is required.

Qualifications

• Bachelor’s degree in Data Science , Computer Science, Bioinformatics, Biomedical Informatics, or a related field . An advanced degree is preferred. We will consider equivalent professional experience in place of a degree.
• At least 5 years building and operating production software or data systems. At least 2 of those years should involve shipping LLM-powered applications (agents, retrieval, or evaluation) that people depend on.
• 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 to decide whether a change was an improvement.
• Experience with structured output and tool or function calling, meaning you have constrained a model to a typed schema and validated 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.
• Technical Skills: Python, FastAPI, Pydantic, pytest; PostgreSQL with vector search; embedding pipelines; Next.js/React/TypeScript; containers and Kubernetes; Git and CI/CD.

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 for a given condition.
• 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 be ready to 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. This covers question and confirmation flows, result presentation, and 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 are all in scope, and you will partner with the operations teams that run those environments instead of standing up parallel cloud infrastructure.
• 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 instead of a one-time measurement.
• Log what the system does and why. Request identifiers, latency, errors, and which concept the system selected all need to be captured, so that staff can review an AI-assisted result instead of taking it on faith.
• Work out what researchers, clinicians, and patient communities need, and turn it into data models, retrieval behavior, and interface design.
• Write the work up . You will contribute to manuscripts, conference abstracts, and posters with NIH investigators, and you will be credited as an author on work you helped produce.

Skills

Python programming

LLM integration

Retrieval systems

Software deployment

Cross-functional collaboration

Education

Bachelor’s degree in Data Science, Computer Science, Bioinformatics, Biomedical Informatics, or a related field. An advanced degree is preferred. We will consider equivalent professional experience in place of a degree.

Tools

PostgreSQL (vector search)

FastAPI

Pydantic

pytest

Kubernetes

Helm

Next.js

React

TypeScript

Job description

Axle, a bioscience and information technology company, seeks a Senior Data Scientist, AI Retrieval Systems to support NIH rare-disease research. This remote, US-based role owns the data layer, retrieval services, interfaces, and deployment on NIH on-prem HPC Kubernetes environments.

You will build ontologies, semantic search, and ranking for clinical concepts, collaborating with NIH program staff and clinical geneticists. Strong LLM, retrieval, and biomedical vocabularies experience is required.