Top AI & Machine Learning Jobs

Lead product strategy and roadmap for ServiceNow's AI Application Development platform. Define multi-year vision, drive developer adoption and GTM, translate AI research into platform primitives, build and scale a senior product organization, and align cross-functionally with engineering, design, and sales to prioritize and deliver enterprise-grade AI application capabilities.

Lead product strategy for ServiceNows AI Application Development platform. Define multi-year vision and roadmap, drive developer adoption and GTM, translate AI-assisted and agentic development into scalable platform primitives, build and grow a senior PM organization, and align cross-functionally with engineering, design, and GTM to deliver enterprise-grade developer and application experiences.

Build, optimize, and scale end-to-end ML infrastructure for training, evaluating, and serving large language models. Develop distributed training and inference pipelines, model evaluation/monitoring, latency optimizations, automation abstractions, and collaborate cross-functionally to productionize state-of-the-art models.

Design, train, evaluate, and productionize LLM-based NLU and agentic AI systems. Improve model quality, latency, reliability, and safety; fine-tune models, implement agent architectures, and collaborate across teams to deploy scalable, privacy-preserving conversational AI.

Lead development and scaling of a generative conversational AI platform: build extensible infrastructure and APIs for chat clients, optimize dialog engine for performance and low memory, implement logging/tracing/metrics and debugging tools, and collaborate with ML and product teams to deliver domain-specific, multilingual enterprise experiences.

Design, build, and optimize scalable ML infrastructure for training, evaluating, and serving large language models. Build abstractions, automation, microservices, and ETL pipelines; collaborate cross-functionally to productionize, monitor, and optimize LLMs and related ML systems.

Lead design and scaling of a generative conversational engine and platform: build scalable APIs, optimize dialog performance and memory/latency, implement logging/tracing/metrics, enable integrations with chat clients, and collaborate with ML and product teams to deliver enterprise-grade agentic AI features.

Design, build, and productionize agentic AI systems (agent orchestration, sandboxed execution, latency optimization, agent memory, LLM self-reflection, knowledge graphs, multimodal I/O). Ship scalable, production-grade code, mentor engineers, and collaborate with ML, security, product, and UX teams to deliver enterprise AI features.

Lead and scale teams to build and operate an AI evaluation platform for internal and customer use. Define strategy and roadmap for benchmarks, automated scoring, verifiers, and monitoring. Drive new evaluation methodologies, architect unified APIs and dashboards, and collaborate with product, engineering, and research to ensure AI quality, safety, and reliability.

Design and deploy machine learning solutions that bring AI into customer workflows (structured and unstructured data) at scale, collaborate with product and engineering, expand ML into new products, own customer-critical features, and mentor the data science team.