Top AI & Machine Learning Jobs

Design and document workflows, business and technical requirements to advance Agentic AI automation for Network Engineering Operations. Incubate and maintain AI/automation roadmap, prototype and pilot solutions with architects and engineering teams, lead case studies and testing, author technical documentation, and collaborate cross-functionally to improve service delivery and assurance. Requires independent judgment and flexible schedules.

Implement and evaluate machine learning models, manage model training and deployment, design data pipelines, build integrations and low-code solutions using AI-assisted tools, and ensure data governance and security while partnering with legal and technology stakeholders.

Lead execution of Comcast Advertising's enterprise AI strategy by translating priorities into plans, coordinating cross-functional initiatives, and driving AI adoption. Manage AI portfolio planning, track KPIs and ROI, support governance and enablement programs, facilitate stakeholder alignment, and ensure delivery across workstreams. Build scalable processes, maintain dashboards and documentation, and support change management, training, and communications to operationalize AI capabilities across the organization.

Lead design and delivery of AI-enabled product capabilities, including agentic workflows, LLM/agent productionization, distributed inference, model lifecycle, and reusable patterns. Drive cross-functional implementation, mentor engineers, improve performance/scalability, and ensure reliable, maintainable customer-facing AI features.

Lead AI engineering strategy and delivery for AI-enabled capabilities, agentic workflows, and intelligent automation. Manage and grow engineering teams, align cross-functional stakeholders, define roadmaps, launch LLM/ML products responsibly to production, and measure business impact while ensuring quality, security, and adoption.

The role involves designing and implementing machine learning systems, mentoring engineers, leading technical strategies, and ensuring system reliability and scalability.

The role involves designing evaluation pipelines for AI agents, establishing benchmarks for performance, and collaborating with product teams. Responsibilities include dataset management, automated evaluations, and mentoring junior engineers.

Design, build, and operate production-grade agentic systems and workflows. Rewrite an existing application into an end-to-end agentic platform using a Google-centric stack (ADK, Gemini). Implement agent-to-agent, agent-to-UI, and human-AI orchestration, AgentOps/MLOps, monitoring, and evaluation (LLM-as-a-Judge). Advocate for ethical, reliable, scalable, and user-centric AI experiences while collaborating with product, UX, and platform teams.

Build, rewrite, and operate production-grade agentic AI systems and workflows. Integrate AI across the SDLC, implement agent-to-agent and agent-to-UI orchestration, ensure reliability, observability, and responsible AI governance, and collaborate with product and UX teams to deliver seamless customer experiences.

Build and operate scalable Golang backend services and APIs for a multimodal ML platform handling video, image, and document processing. Integrate ML/LLM inference, agentic workflows, and vector retrieval (Milvus). Deploy and manage services on Kubernetes with Terraform on AWS, ensure observability, reliability, and security, and collaborate with ML engineers to productionize pipelines and run on-call/incident response.