Back
Strong employer brand, mid-level generalist ML/data role in a metro with broad skill requirements.
Core ML and data engineering skills transfer broadly, but consumer healthcare and privacy needs add domain specificity.
Explicit 3–6 years and many mandatory ML, cloud, and full-stack technologies.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Build and deploy AI models focused on personalization, anomaly detection, and predictive health insights using real-time sensor data and user behavior patterns.
Collaborate with business units, centers of excellence, and cloud teams to integrate AI into consumer-facing applications and business platforms.
Implement software development lifecycle (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.
3–6 years of experience in data engineering and AI development, preferably in consumer technology.
Strong proficiency in Python, fine-tuning large language models (LLMs), TensorFlow or PyTorch, SQL; experience with cloud platforms (Azure/GCP), cloud-native development, containers, and Kubernetes.
Practical experience in full-stack development using Next.js, Node.js, and React; familiarity with consumer data privacy standards like GDPR and CCPA.
Office-based role requiring in-person presence at least 3 days per week.
Experienced in engineering scalable AI/ML solutions tailored to consumer health products with real-time data streams.
Skilled in cross-team collaboration involving business units, cloud, and AI centers to integrate and deploy AI capabilities into applications and platforms.
Proficient in both backend AI model deployment and frontend full-stack development to deliver AI-driven user experiences under strict data privacy compliance.