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Remote role and broad AI title increase applicant density, but senior specialisation and healthcare focus moderate competition.
Healthcare-focused AI experience and regulated data requirements demand domain-specific backgrounds.
Explicit 8+ years requirement and mandatory Python/PySpark make shortlisting highly strict.
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Design, build, deploy, and scale end-to-end AI solutions focused on Generative AI, NLP, and healthcare applications.
Own full AI model lifecycle including data prep, experimentation, deployment, monitoring, and continuous improvement aligned with Responsible AI guidelines.
Lead and mentor data science and AI engineering teams across multiple geographies, driving best practices and technical quality.
8+ years experience developing and implementing ML and AI solutions.
5+ years hands-on experience with NLP, deep learning, and transformer-based models; 2+ years practical experience with Generative AI including LLM workflows and Retrieval-Augmented Generation (RAG).
Strong proficiency in Python and PySpark; proven experience building production-grade ML/AI systems at scale.
Work Experience Required: 8+ years; Mentioned required technical skills and domain-specific experience in healthcare and AI deployment.
Technical leader skilled in translating complex business and healthcare problems into structured, measurable AI solutions with clear business impact.
Experienced in healthcare domain AI use cases including clinical AI, payer/provider analytics, and regulated environments with knowledge of privacy and Responsible AI.
Experienced in managing cross-functional teams, operating in ambiguous and matrixed organizational settings with strong communication and stakeholder influence abilities.