Top AI & Machine Learning Jobs

Lead design, development, deployment, and maintenance of AI/ML solutions (LLMs, generative models, predictive analytics) and conversational agents. Integrate AI features with web/APIs and cloud infrastructure, ensure responsible AI, security, and operational excellence, mentor team members, and partner with product and architecture to deliver scalable healthcare solutions.

Lead architecture and technical strategy for an agentic AI claims automation platform. Define end-to-end architecture, enable multi-agent workflows, integrate models and MLOps, ensure governance, resilience, observability, and cost efficiency, and mentor architects while aligning with enterprise AI standards.

Lead design, development, deployment, and maintenance of responsible AI/ML solutions (including LLMs, generative models, chatbots, and agent orchestration) for provider-facing products. Provide technical leadership, mentor engineers, align solutions with enterprise AI strategy and compliance, integrate AI into cloud architectures, and ensure production reliability and operational excellence.

Design, build, and deploy end-to-end scalable AI/ML solutions (classical ML, NLP, generative AI, RAG). Implement MLOps/CI-CD, productionize models, monitor performance, mentor engineers, and align solutions with business objectives while applying Responsible AI practices.

Lead design, build, and operationalize production-grade AI/ML systems end-to-end: data, modeling, MLOps, deployment, monitoring, and responsible AI. Mentor engineers, partner with product and clinical teams, and drive observability, security, and measurable clinical/operational outcomes.

Design, build, and maintain scalable full-stack applications using Java, TypeScript/React, and Python. Develop backend services, RESTful APIs, microservices, and AI integrations. Implement agentic AI capabilities, LLMs, RAG, embeddings, and vector search. Collaborate with product, data science, UX, QA, security, and DevOps; participate in code reviews, testing, CI/CD, and apply secure engineering and responsible AI principles.

Lead technical direction and people for an AI/ML engineering squad to design, build, and deploy production-grade ML and Generative AI (LLMs, RAG, agentic systems). Drive MLOps, CI/CD, model monitoring, Responsible AI compliance (HIPAA/PHI), architecture reviews, and mentor 5–10 engineers to deliver secure, production solutions.

Design, build, and maintain scalable full-stack applications (Java/TypeScript/React/Python). Develop backend services, APIs, microservices, and agentic AI capabilities integrating LLMs, RAG, embeddings, and vector search. Collaborate with product, data science, QA, security, and DevOps; apply secure engineering, CI/CD, testing, performance optimization, and enterprise compliance.

Design, build, and productionize generative AI, LLM, RAG, and agent-based systems for healthcare. Develop and fine-tune LLM applications, implement vector search and ingestion pipelines, create evaluation/monitoring and safety/governance controls, and collaborate with product and data teams to deliver scalable, reliable AI solutions in cloud-native environments.

Lead design, build, and operate end-to-end AI/ML-enabled full-stack applications for clinical workflows. Develop Next.js/React frontends, Node.js backends, PostgreSQL data models, integrate LLM capabilities, deploy and monitor on Azure, implement CI/CD and security best practices, and mentor engineers.