Senior Data, AI Engineer

Job not on LinkedIn

🔥 12 hours ago

🏄 California – Remote

🏄 California – Remote

💵 $145k - $187k / year

⏰ Full Time

🟠 Senior

🤖 AI Engineer

👻 Ghost score 0%

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CareDx, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

🏥 Healthcare

💼 Consulting

📦 Logistics

Healthcare • Consulting • Logistics

<CareDx, Inc. > CareDx, Inc. is a healthcare-focused company that develops diagnostic tests, laboratory services, and digital solutions specifically for transplant patients and providers. Its offerings include cell-free DNA tests (AlloSure) for monitoring organ injury, HLA typing products for matching, transplant lab services, digital patient management apps and EMR integrations, and pharma services to support clinical development. CareDx serves transplant centers, clinicians, patients, and biopharma partners to improve organ transplant outcomes across kidney, heart, and lung care.

📋 Description

• 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

• 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

• 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

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