Senior Data, AI Engineer

CareDx, Inc.

. Design, implement, test, deploy, and maintain pipelines integrating structured EMR data and processing unstructured clinical narratives .

Posted 11/4/2026full-timeRemote • California • United StatesSenior💰 $145,000 - $187,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and implementing clinical NLP solutions, integrating structured EMR data, and utilizing advanced machine learning techniques. Proficient in managing data quality, compliance with healthcare regulations, and mentoring engineering teams.

Highest-signal resume keywords

Clinical NLP Solutions DevelopmentAdvanced Python and SQL SkillsExperience with OMOP Common Data ModelTransformer Models Using PyTorch or TensorFlowEntity Recognition and Relationship Extraction

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

NLPMachine LearningEntity RecognitionRelationship ExtractionData NormalizationETL WorkflowsAPIsClinical Context InterpretationStatistical or Deep Learning ModelsAutomated Data-Quality Checks

Soft Skills

MentoringTechnical CommunicationProblem-Solving

Tools & Technologies

MedspaCyScispaCyCTAKESHugging Face TransformersGitCI/CDHL7 FHIRHL7 v2Cloud PlatformsPandas

Industry Keywords

ICDSNOMED CTRxNormLOINCUMLSOMOP CDMClinical WorkflowsHealthcare Data ComplianceHIPAAClinical Error Analysis

Tech Stack

Tools & technologies

CloudETLPandasPythonPyTorchSQLTensorflow

About the role

Key responsibilities & impact

Design, implement, test, deploy, and maintain pipelines integrating structured EMR data and processing unstructured clinical narratives
Develop entity and relationship extraction workflows for diagnoses, symptoms, laboratory results, demographics, medications, allergies, and procedures
Normalize clinical concepts using ICD, SNOMED CT, RxNorm, LOINC, and other terminologies
Implement clinical context interpretation for negation, uncertainty, temporality, experiencer, and treatment status
Reconcile extracted findings with structured EMR records using source and time precedence rules
Build and evaluate hybrid clinical NLP approaches using rules, dictionaries, statistical or deep learning models, and LLMs
Partner with clinicians on schemas, source mappings, annotation guidelines, reference datasets, and acceptance criteria
Measure extraction and normalization performance and conduct clinical error analysis
Preserve source evidence, provenance, model and terminology versions, and review status
Build ETL workflows, APIs, and validation controls for EMR and NLP data
Monitor data quality, throughput, reliability, and model performance; resolve production issues
Design and maintain mappings and transformation pipelines for a transplant-focused OMOP CDM
Document architecture and operational procedures, lead code and design reviews, mentor engineers, and communicate technical tradeoffs
Follow security, privacy, and compliance requirements for sensitive healthcare data, including HIPAA-aligned practices

Requirements

What you’ll need

Master’s or Ph.D. degree in Computer Science, Computational Linguistics, Biomedical Informatics, Data Science, Engineering, or a related field, or equivalent practical experience
7+ years of relevant experience in NLP, machine learning, or applied AI engineering
3+ years developing clinical NLP solutions using real-world EHR or hospital notes, with demonstrated delivery of production solutions
Advanced Python and SQL skills
Experience with pandas or comparable data-processing tools, relational data modeling, ETL orchestration, incremental processing, schema validation, and automated data-quality checks
Experience integrating structured EMR data through HL7 FHIR, HL7 v2, APIs, or database extracts
Experience with the OMOP Common Data Model and OHDSI standardized vocabularies
Experience validating OMOP data for conformance, completeness, and plausibility
Experience with clinical entity recognition and linking, relationship extraction, assertion detection, and temporal extraction
Experience with medspaCy, scispaCy, cTAKES, or comparable frameworks
Expertise with ICD, SNOMED CT, RxNorm, LOINC, UMLS, and UCUM or equivalent methods
Experience with transformer models using PyTorch, TensorFlow, or equivalent frameworks and Hugging Face Transformers or comparable tooling
Experience with LLM-based clinical extraction, schema-constrained outputs, and terminology-grounded validation
Strong understanding of medical terminology, diseases, laboratory measurements, medications, and clinical workflows
Experience creating clinician-reviewed reference datasets and annotation guidelines
Experience measuring precision, recall, and F1
Experience preventing patient-level data leakage and evaluating performance across source systems and note types
Experience building production APIs or services and deploying containerized applications on a cloud platform
Experience with Git, automated testing, CI/CD, model and data versioning, monitoring, batch inference, error recovery, and performance testing
Ability to lead technical work independently, mentor engineers, document designs, and communicate tradeoffs clearly

Benefits

Comp & perks

Competitive base salary and incentive compensation
Health and welfare benefits
Gym reimbursement program
401(k) savings plan match
Employee Stock Purchase Plan
Pre-tax commuter benefits
Up to 30 days of paid leave annually for a full-time employee who donates an organ or bone marrow
Additional discretionary bonuses/incentives and restricted stock units may be available