← All roles

Senior Data & AI Engineer

CareDx· IT & SOFTWARE OPERATIONS
Apply on company site
Hybrid (Brisbane, CA)$145k - $187kfull-timePosted 1w ago

About the role

Senior hands-on technical owner for solutions that transform structured and unstructured data from real-world EMRs into reliable, standardized clinical data. Designs and delivers data engineering and clinical NLP pipelines to integrate and normalize diseases, diagnoses, labs, demographics, meds, procedures, and other clinical information for transplant-focused data models and production systems.

Responsibilities

  • Own the design, implementation, testing, deployment, and maintenance of pipelines that integrate structured EMR data and process unstructured clinical narratives.
  • Develop entity and relationship extraction workflows for diagnoses, symptoms, laboratory results, demographics, medications, allergies, and procedures, linking findings to relevant values, units, doses, routes, frequencies, anatomical sites, and dates.
  • Normalize structured source codes and extracted clinical concepts using ICD, SNOMED CT, RxNorm, LOINC, and other terminologies; manage local codes, synonyms, abbreviations, ambiguous mappings, terminology versions, and hospital-specific language.
  • Implement clinical context interpretation, including negation, uncertainty, temporality, experiencer, and treatment status. Distinguish current conditions from historical, family, hypothetical, and ruled-out findings.
  • Handle clinical note structure, copied-forward content, conflicting statements, and information spanning sentences or encounters. Reconcile extracted findings with structured EMR records using defined source and time precedence rules while retaining discrepancies, source evidence, and clinical timelines.
  • Build and evaluate hybrid approaches using rules, dictionaries, statistical or deep learning models, and LLMs; apply structured output validation and terminology checks to prevent unsupported facts and invalid codes.
  • Partner with clinicians to define clinical data schemas, source mappings, annotation guidelines, reference datasets, and acceptance criteria; resolve annotation disagreements and translate clinical requirements into engineering specifications.
  • Measure entity, relationship, assertion, and normalization performance; conduct clinical error analysis and validate generalization across hospitals, specialties, and note types using patient-level data separation and checks for data leakage.
  • Preserve source text, note and encounter identifiers, extraction provenance, model and terminology versions, and review status. Establish confidence thresholds and human review workflows for ambiguous or high-impact outputs.
  • Build ETL workflows, APIs, and validation controls to harmonize structured EMR fields and NLP outputs, including patient and encounter linkage, units, timestamps, and duplicate records; monitor data quality, throughput, reliability, and model performance, and resolve production issues.
  • Document architecture and operational procedures, lead code and design reviews, mentor engineers, and communicate technical tradeoffs to clinical, scientific, product, and engineering stakeholders.
  • Follow security, privacy, and compliance requirements for sensitive healthcare data, including HIPAA-aligned practices, least-privilege access, appropriate logging, and secure data handling.
  • Design and maintain mappings and transformation pipelines for a transplant-focused OMOP CDM, representing transplant procedures, donor and recipient information, immunosuppressive therapies, laboratory results, rejection episodes, and longitudinal outcomes using appropriate standard concepts and documented extensions where needed.

Qualifications

  • Master’s or Ph.D. in Computer Science, Computational Linguistics, Biomedical Informatics, Data Science, Engineering, or related field, or equivalent practical experience.
  • 7+ years of relevant NLP, ML, or applied AI engineering experience, including 3+ years developing clinical NLP solutions with real-world EHR notes and production delivery.
  • Advanced Python and SQL skills with pandas, relational modeling, ETL orchestration, incremental processing, schema validation, and automated data-quality checks.
  • Hands-on experience integrating structured EMR data via HL7 FHIR, HL7 v2, APIs, or database extracts; align patient/encounter records, normalize units/time, manage duplicates, reconcile conflicting sources.
  • Hands-on experience with OMOP CDM and OHDSI vocabularies; source-to-standard concept mapping, vocabulary relationships, ETL to transform EMR data and NLP outputs into OMOP tables.
  • Experience validating OMOP data for conformance, completeness, plausibility, with traceable source mappings and quality controls for longitudinal data.
  • Clinical entity recognition and linking, relationship extraction, assertion detection, temporal extraction, including sentence/section detection, abbreviation disambiguation, negation, uncertainty, and experiencer.
  • Experience implementing clinical NLP pipelines with medspaCy, scispaCy, cTAKES, or similar; combining rules, dictionaries, and ML based on task requirements.
  • Practical expertise with ICD, SNOMED CT, RxNorm, LOINC, and UMLS; terminology services, value sets, semantic types, ontology hierarchies, concept retrieval, local-code crosswalks, and terminology version management; unit normalization with UCUM.
  • Experience applying transformer models (PyTorch/TF) and Hugging Face; hands-on with LLM-based clinical extraction, schema-constrained outputs, and terminology-grounded validation.
  • Strong understanding of medical terminology, diseases, labs, medications, and workflows; ability to interpret documentation and identify ambiguous findings for clinician review.
  • Experience creating clinician-reviewed reference datasets and annotation guidelines; measuring precision/recall/F1 for extraction/normalization/assertion; preventing patient-level leakage; evaluating across sources and notes.
  • Experience building production APIs/services, deploying containerized apps on cloud, and using Git, CI/CD, model/data versioning, monitoring, batch inference, error recovery, and performance testing.
  • Proven ability to lead technical work independently, mentor engineers, document designs and procedures, and communicate tradeoffs to clinicians and stakeholders.

Skills

Required:PythonSQLNLP for clinical dataOMOP CDM

Benefits

  • Competitive base salary
  • Health and welfare benefits including gym reimbursement
  • 401(k) match
  • Employee Stock Purchase Plan
  • Pre-tax commuter benefits
  • Living Donor Employee Recovery Policy (up to 30 days for donors)
Last updated Oct 14, 2026. Interested? Apply on the company site.
CareDx logo

About CareDx

Together in Transplant

CareDx delivers transplant-focused diagnostics, digital health tools, and services that support patients and clinicians across the entire transplant journey.

DiagnosticsDigital HealthTransplant
Company profileWebsite

More open roles at CareDx