Top AI & Machine Learning Jobs

Lead enterprise AI transformation engagements combining C-suite advisory, solution architecture, and change management. Design end-to-end AI architectures (RAG, knowledge graphs, Now Assist), data catalog strategies, governance, and adoption plans. Drive pilot delivery, reusable practice assets, and measurable value realization across complex, multi-stakeholder enterprise programs.

Lead a team building evaluation infrastructure and benchmarks for agentic and generative AI. Design automated tests, validate RAG pipelines, benchmark frontier LLMs, and translate evaluation results into product and risk recommendations to ensure reliable, safe, and cost-effective autonomous workflows.

Lead a team to measure and improve enterprise search relevance and ranking using ML and LLM/RAG techniques. Manage end-to-end model development, evaluation, deployment, cross-functional collaboration, and team growth to ensure scalable, production-grade search quality.

Own and build the agent execution harness and orchestration runtime for enterprise-scale conversational/agentic AI: ensure reliability, observability, prompt/version management, LLM integration, eval frameworks, cost/latency optimization, and provide technical leadership for safe, production-grade agent workflows.

Build and improve enterprise conversational search and question-answering systems using IR and generative AI. Implement retrieval, matching, ranking, and summarization across heterogeneous knowledge sources, develop LLM-enabled features, and create evaluation metrics addressing enterprise constraints like security, privacy, and scalability.

Improve enterprise search relevance for a question-answering platform by crafting and optimizing ranking features, building algorithm frameworks, enabling parallel ranking experiments with tooling, analyzing query logs, and developing metrics to evaluate and boost answer quality across heterogeneous knowledge sources.

Lead enterprise AI transformation and architecture engagements from strategy through delivery. Advise executives on AI roadmaps, design end-to-end AI and data architectures (including knowledge graphs, data catalogs, RAG, and integrations), establish governance and responsible AI practices, drive adoption and change management, and develop reusable practice assets and thought leadership to realize business value.

Lead engineering and product efforts to design and implement Agentic AI and conversational/web features using LLMs. Collaborate with ML experts, PM, UX, and GTM to scope, deliver, and scale enterprise AI product capabilities across customers and markets while mentoring engineers and shaping product direction.

Build and productionize agentic AI systems using LLMs. Contribute to agent orchestration, sandboxed execution, latency optimization, agent memory, and multimodal I/O. Collaborate with ML, security, product, and UX teams, mentor engineers, and drive roadmap and scalable infrastructure to deliver reliable enterprise AI features.

Lead product strategy and execution for an enterprise-scale AI-powered search platform. Own platform scalability, search quality metrics, ML performance tradeoffs, cross-functional roadmaps, and translate ambiguous user needs into clear specs and success metrics to deliver performant, enterprise-grade AI search features at scale.