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Tier-1 brand, metro location, and a visible data/AI title produce moderate applicant competition.
Core data engineering and ML skills transfer across industries, though consumer-health privacy adds moderate domain sensitivity.
Explicit 7+ years requirement plus mandatory AI, cloud, and deployment tech stack increases filter strictness.
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Build scalable data pipelines and deploy AI models for personalization, anomaly detection, and predictive health insights within consumer health products.
Collaborate with business units, centers of excellence, and cloud teams to integrate AI into consumer-facing applications, business processes, and platforms.
Implement Software Development Life Cycle (SDLC) practices for continuous delivery and monitoring of AI models while ensuring compliance with consumer data privacy regulations.
Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field.
7+ years overall experience with 3-6 years specifically in data engineering and AI development, preferably in consumer technology domain.
Strong proficiency in Python, fine-tuning large language models (LLMs), TensorFlow/PyTorch, SQL, and experience with cloud platforms (Azure or GCP) including containerization and Kubernetes for AI workloads.
Office-based role requiring at least 3 days per week presence at company facilities; familiarity with consumer data privacy standards such as GDPR and CCPA.
Experienced in full-stack development using Next.js, Node.js, and React to build AI-driven user interfaces and applications.
Senior-level data and AI engineer with domain expertise in consumer technology and AI integration into products and platforms.
Comfortable working in collaborative environments involving multiple teams (BU, COE, cloud) with strong focus on SDLC and regulatory compliance.