Top AI & Machine Learning Jobs

Lead development of a generative-AI-enabled enterprise search platform: architect abstractions, build ranking and multi-turn QA systems, integrate LLM and RAG features, create evaluation metrics, and mentor engineers and hiring processes.

Lead measurement and forecasting of core product and engineering metrics using statistical and ML methods; build scalable data pipelines, evaluation pipelines for LLM/agentic systems, and self-serve analytics. Mentor junior data scientists and drive cross-functional alignment to translate insights into business KPIs.

Design and build the agent execution harness, ensure runtime reliability and observability at scale, build prompt/versioning systems, design evaluation frameworks, integrate frontier LLMs, and provide technical leadership for production agentic AI systems.

Lead enterprise AI transformation engagements as a senior strategic and technical advisor. Advise executives on AI strategy, design end-to-end AI and data architectures (RAG, knowledge graphs, MCP), architect data catalog and metadata strategies, embed AI governance and responsible AI controls, and drive adoption, change management, and practice development across customers.

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.

Lead enterprise AI transformation and solution architecture engagements from strategy through delivery. Advise executives, design end-to-end AI and data architectures (RAG, knowledge graphs, data catalogs), define governance and responsible AI frameworks, drive adoption and change management, and develop reusable practice IP and playbooks to scale AI across the ServiceNow platform.

Design and scale Moveworks' generative conversational platform: build product infrastructure, APIs, and optimizations for low-latency, memory-efficient dialog engines; implement logging/tracing/metrics; enable multilingual, domain-specific experiences; and collaborate with ML, product, and support teams to deliver robust enterprise AI at scale.

Lead discovery, design, and delivery of Agentic AI POCs on the ServiceNow platform in 3-4 week sprints. Scope and run consultative workshops, configure AI agents, integrate enterprise data sources, build reusable prompt libraries and agent templates, support sales technical positioning, and orchestrate engineers to produce production-ready prototypes and handoffs.

Build and productionize agentic AI systems for enterprise scale, working on agent orchestration, sandboxed execution, latency optimization, memory and self-reflection, knowledge graphs, and multimodal I/O. Partner across ML, security, product, and UX, mentor engineers, and deliver robust, performant code and product improvements.

Design, build, and operate production-grade agentic AI systems that sense enterprise data, decide with frontier models, act across workflows, and govern safely at Fortune 500 scale. Focus on multi-agent orchestration, retrieval/RAG grounding, model integration, observability, and technical leadership.