Lead global AI and Machine Learning (ML) initiatives supporting continuous glucose monitoring (CGM) medical device business ecosystems.
Full Time. See below for experience and education. 40 hrs/week. Position may require work in various and unanticipated work locations throughout U.S. Telecommunication is permissible. Up to 25% travel, domestic or international, may be required to various and unanticipated sites.
Requirements:
Bachelors or foreign equivalent in Computer Science, Engineering, Data Science, Information Systems, Business Analytics or a related scientific, technical or business field of study with minimum 6 years of progressive professional experience in Natural Language Processing (NLP), AI, Machine Learning (ML), data analytics, digital product management, software engineering, or technology delivery. Alternatively will accept Masters with minimum 4 years of professional experience in NLP, AI, ML, data analytics, digital product management, software engineering or technology delivery. Each alternative requirement must possess minimum 3 years of professional experience in each of the following: (i) enhancing data privacy & compliance through implementation of advanced NLP techniques & ensure compliance with GDPR and CCPA regulations; (ii) leveraging advanced models, identifying patterns & predicted business engagement outcomes, enabling data-informed decision-making; (iii) delivering AI-driven solutions that reduce business risks & foster safer business practices; (iv) Cloud Systems, including AWS and Google Cloud; (v) Docker and Kubernetes; (vi) ML and NLP Libraries, including NLTK, SpaCy, Flair, Matplotlib, or related; & (vii) Pandas, PyTorch & TensorFlow. Must possess an academic or industrial background in: (viii) building production-grade ML pipelines & managing Continuous Integration/Continuous Deployment (CI/CD) workflows for model deployment; (ix) healthcare AI governance by implementing model validation, drift detection & data quality monitoring to ensure reliability of AI systems in a clinical environment; & (x) utilizing NLP to analyze transcripts, automate identification & optimizing workforce efficiency through data-driven agent support & training recommendations. Employer will accept any suitable combination of education, training, or experience.
An EOE.
Application Method:
Send resumes to [email protected] or by mail to Abbott Laboratories, Attn: 26J14A, Willis Tower, 233 S. Wacker Dr., Floor 26, Dept. 32, Chicago, IL 60606. Refer to ad code: ABT-0193-ES.
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