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Tier-1 brand, popular ML title, and metro location increase candidate competition.
Healthcare data and HIPAA compliance requirements create high industry-specific background sensitivity.
Explicit years, mandatory Python/ML frameworks, and healthcare domain/HIPAA requirements increase filter strictness.
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Develop, deploy, and maintain machine learning models and AI solutions targeting healthcare use cases including EHR, claims, and clinical text data.
Build end-to-end ML pipelines covering data preparation, feature engineering, model training, evaluation, and deployment, adhering to healthcare compliance (e.g., HIPAA) and MLOps standards.
Collaborate cross-functionally to translate healthcare AI requirements into scalable, impactful solutions and communicate analytical insights to stakeholders clearly.
Bachelor's degree in Computer Science, AI/ML, Data Science, Statistics, or related field.
At least 1 year of professional experience in machine learning, AI development, or data-driven engineering.
Proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch; experience with data tools like Pandas, NumPy, and SQL.
Mandatory healthcare domain experience with exposure to EHR/EMR, claims, or clinical datasets.
Experience working with healthcare-specific data and familiarity with HIPAA and healthcare compliance in AI/ML projects.
Strong practical skills in applying AI/ML techniques including NLP, deep learning, GenAI, LLMs, and predictive modeling to real-world healthcare problems.
Ability to build scalable ML pipelines and communicate technical insights effectively to diverse stakeholders in a regulated environment.