Job Title: GenAI/ML Engineering Lead Location: Hybrid (Preferred in San Jose, CA or open to relocation within the U.S.) Employment Type: Contract (C2C or W2) Work Authorization: US Citizens or H4 EAD only Experience Required: 12+ Years Job Overview We are seeking a seasoned GenAI/ML Engineering Lead to join a high-impact digital health initiative with a focus on building scalable, privacy-first AI systems. The ideal candidate will have hands-on experience architecting and deploying Generative AI and ML-powered platforms, with proven success in driving innovation at the intersection of healthcare, compliance, and cloud-native technologies. Key Responsibilities • Design and deploy end-to-end Generative AI (GenAI) solutions using models such as GPT-3, LLaMA, and related transformer-based architectures. • Develop and lead ML strategy for real-time, AI-powered healthcare platforms. • Build and operationalize cloud-native microservices (AWS/GCP) with CI/CD pipelines and MLOps best practices. • Collaborate cross-functionally with product, engineering, compliance, and clinical teams to align AI capabilities with business goals. • Ensure product scalability, compliance, and security by embedding HIPAA, SOC2, HITRUST, and GDPR standards from design to deployment. • Lead integration with EHR systems using HL7/FHIR standards for real-time health data exchange. • Optimize and scale AI/ML models for both edge and cloud environments to support predictive healthcare interventions. Required Skills & Expertise • Strong hands-on experience with GenAI, including NLP, audio processing, and conversational AI. • Expertise in Python, TensorFlow, Docker, Kubernetes. • Advanced knowledge of MLOps, CI/CD, model deployment, monitoring, and testing. • Experience designing cloud-native architectures on AWS and GCP. • Strong understanding of privacy regulations (HIPAA, GDPR, HITRUST, SOC2) and secure software development. • Familiarity with real-time data processing systems and healthcare integrations using HL7/FHIR. • Proven leadership experience managing engineering/product teams in agile environments. Preferred Qualifications • Experience in scaling AI/ML systems for remote patient monitoring or clinical applications. • Background in building AI frameworks that support both cloud and edge deployments. • Demonstrated ability to deliver AI-powered user experiences in regulated environments. Submission Notes Please include the following with your application: • Job Title • Visa Status • Current Location • Willingness to Relocate • Consent to share Visa Copy and Driver’s License