Top AI & Machine Learning Jobs

Design, build, and operate enterprise AI systems and platforms for LLMs, RAG, and agentic AI. Lead architecture, MLOps/LLMOps pipelines, model deployment, scalable backend services, observability, and governance. Mentor teams and integrate AI capabilities into enterprise applications while ensuring reliability, security, and compliance.

Lead end-to-end delivery of AI/ML programs: define roadmaps, manage cross-functional teams, ensure scalable production models, enforce governance/responsible AI, optimize costs, and deliver measurable business outcomes while contributing hands-on to AI/ML systems and research translation.

Lead end-to-end delivery of AI-powered chatbot (Optum Assistant) projects, managing scope, schedules, budgets, risks, governance, and cross-functional coordination across clinical, technical, and operational teams.

Lead end-to-end delivery of AI/ML programs: define roadmaps, manage cross-functional teams, ensure production reliability and compliance, govern responsible AI, control costs, and deliver measurable business outcomes.

Design, build, deploy, and scale enterprise AI/ML and Generative AI systems. Implement MLOps/LLMOps, data pipelines, model training/deployment, monitoring, and integrations (APIs, microservices). Operationalize LLMs, RAG, agentic workflows, and optimize for performance, reliability, and cost while ensuring governance and Responsible AI compliance.

Lead end-to-end delivery of AI-native applications and platforms, embedding AI-assisted development, enforcing cloud-native microservices and CI/CD practices, managing multi-stream global teams and vendor integrations, translating business needs into scalable solutions, and ensuring security, compliance, and Responsible AI across delivery.

Lead design and delivery of scalable production AI/ML solutions across the full lifecycle: data preparation, feature engineering, model development, deployment, monitoring, and drift analysis. Build ML pipelines, ensure Responsible AI, guide architecture and governance, and collaborate with engineering, product, and data teams to operationalize models on multi-cloud infrastructure.

Design, build, and productionize generative AI/NLP solutions (LLMs, RAG, agents) for enterprise healthcare use cases. Develop, fine-tune, and optimize models, implement ingestion/embedding/vector DB pipelines, establish evaluation/monitoring and responsible AI controls, and collaborate with product and platform teams to deploy scalable, observable ML systems.

Lead the design and delivery of AI platforms, manage technical teams, ensure security, and mentor talent in a cloud environment.

Lead the design and delivery of AI/ML solutions for healthcare. Oversee end-to-end project management, mentor team members, and ensure compliance with data privacy. Engage with stakeholders for problem-solving and technical roadmaps.