Top AI & Machine Learning Jobs

Lead design and delivery of AI solutions from concept to production: identify high-impact opportunities, shape solution approach with engineering and data science, document tradeoffs, coordinate cross-team integration into product workflows, apply AI-assisted discovery to accelerate requirements, and present outcomes to technical and executive stakeholders.

Design, develop, and deploy AI/ML solutions focusing on deep learning and conversational AI, leveraging cloud-native architecture on Google and AWS platforms.

Lead AI strategy and program management across business units, co-lead enterprise innovation forums from ideation to implementation, drive process reimagination using AI, ensure execution readiness for AI-first initiatives, and collaborate with operations, data, AI and technology stakeholders to scale AI solutions and measure impact.

Lead AI product strategy for Revenue Cycle Management commercial services, owning roadmap, P&L, and full product lifecycle. Drive AI-powered solution development, cross-functional execution, market insights, adoption, pricing, and sales/growth enablement while influencing senior leaders and stakeholders.

Develop AI approaches for healthcare, build and test ML models, conduct experiments, analyze data, and collaborate on solutions.

Lead design and implementation of AI-powered web applications and agentic workflows. Architect scalable full-stack solutions integrating LLMs, microservices, databases, and cloud deployments. Promote AI-assisted development, enforce responsible AI governance, mentor engineers, and deliver production-grade AI SaaS features using no-code/low-code and advanced platforms.

As a Senior AI/ML Engineer, you will design and build end-to-end ML systems, manage ML lifecycle workflows, and ensure compliance with AI standards within the healthcare sector.

Design, build, and deploy production AI/GenAI solutions including agentic systems and RAG pipelines. Integrate LLMs with enterprise systems via APIs and microservices, implement prompt engineering and orchestration, ensure observability and performance, and mentor peers while evaluating emerging AI tools.

Support development and deployment of AI solutions including building and tuning ML/NLP models, implementing RAG pipelines and search systems, writing Python data pipelines, and integrating models in cloud environments.

Lead design, development, and deployment of scalable AI/ML and NLP solutions, including intelligent agents and prompt engineering. Mentor team members, integrate with MCP servers for large-scale AI computations, ensure ethical AI practices, collaborate cross-functionally, and translate research into production-ready capabilities while maintaining data privacy and security compliance.