CalTek is an engineering and technical staffing agency that is one of the country’s leading healthcare recruitment firms. Our client is a leading Healthcare AI company revolutionizing the medical revenue cycle through cutting-edge artificial intelligence and machine learning technologies. Their proprietary platforms power clinical documentation improvement (CDI), automated coding, and claims optimization for top hospitals and healthcare organizations across the U.S. By applying deep NLP and advanced analytics to unstructured medical data, they help providers reduce administrative burden, maximize reimbursement, and enhance patient outcomes.
Join a team of AI pioneers, data scientists, and healthcare innovators passionate about transforming the future of healthcare through intelligent automation and real-time decision support.
Typical Duties and Responsibilities
As a Senior NLP Engineer, you will be responsible for architecting, building, and refining natural language understanding and generation models that power our AI-driven revenue cycle products. Your work will involve:
- Designing and deploying NLP pipelines for medical text classification, entity recognition, and information extraction
- Training large-scale language models (e.g., BERT, BioBERT, ClinicalBERT, RoBERTa) on domain-specific corpora
- Creating algorithms for ICD-10, CPT, and DRG code prediction using clinical notes and EHR data
- Developing and optimizing ontology-based mapping tools leveraging UMLS, SNOMED CT, and LOINC
- Collaborating with data scientists, annotators, and clinical informaticists to label datasets and validate model outputs
- Integrating NLP modules into scalable cloud-based architectures using APIs and microservices
- Monitoring and improving model performance through A/B testing, fine-tuning, and error analysis
- Publishing results and contributing to the organization’s IP and thought leadership in AI for healthcare
Education
- Bachelor’s degree in Computer Science, Computational Linguistics, Data Science, or related technical field (required)
- Master’s or PhD in Machine Learning, Natural Language Processing, or a related domain (strongly preferred)
Required Skills and Experience
- 10+ years of professional experience in NLP, with at least 3+ years in healthcare-specific NLP applications
- Strong background in machine learning, deep learning, and statistical NLP methods
- Proficiency in Python with experience in libraries such as TensorFlow, PyTorch, Hugging Face Transformers, spaCy, NLTK, and Scikit-learn
- Experience working with EMR/EHR datasets (e.g., Epic, Cerner), clinical narratives, and medical coding systems
- Demonstrated expertise in building and maintaining production-grade NLP systems in cloud environments (AWS, Azure, or GCP)
- Strong understanding of HIPAA compliance, PHI data handling, and security best practices in healthcare AI
- Familiarity with MLOps tools such as MLflow, DVC, Airflow, Docker, and Kubernetes for model deployment and lifecycle management
- Experience with FHIR standards, HL7 messaging, and healthcare interoperability protocols
- Excellent communication and documentation skills to collaborate with cross-functional teams and stakeholders
Preferred Qualifications
- Experience with large language models (LLMs) and foundation models applied to healthcare
- Prior work in medical claim denial prediction, clinical documentation improvement, or automated medical coding
- Familiarity with knowledge graphs, semantic search, or retrieval-augmented generation (RAG)
- Contributions to open-source NLP libraries or peer-reviewed publications in computational linguistics or biomedical informatics
- Exposure to regulatory frameworks such as FDA AI/ML guidance, SaMD, or ONC health IT certifications
