Top AI & Machine Learning Jobs

Build and productionize scalable ML infrastructure for training, evaluating, and serving large language models. Develop distributed training and inference pipelines, optimize LLM latency, create automation abstractions, and collaborate cross-functionally to scale ML systems and best practices.

Build and scale Moveworks' conversation engine for enterprise generative AI: design scalable APIs, optimize dialog performance and memory/latency, implement logging/tracing and monitoring, enable multilingual translation and domain-specific experiences, create engineer-facing product infrastructure, and collaborate with ML, product, and support teams.

Design, scale, and optimize a generative conversational AI platform and conversation engine for enterprise use. Build product infrastructure and APIs, improve performance and memory/latency, implement logging/tracing/metrics, enable domain-specific and multilingual experiences, and collaborate with ML, product, and support teams to deliver robust, scalable solutions.

Lead development of scalable analytics and evaluation systems for LLM and AI-powered products. Partner with execs, product, and engineering to define metrics, apply statistical and ML methods to measure and forecast product and system performance, automate analyses and self-serve insights, and mentor junior data scientists while owning evaluation pipelines and AI-native integrations.

Scale and optimize a generative conversation engine for enterprise use: build product infrastructure and APIs, optimize dialog performance and memory, enable multilingual support, implement logging/tracing/metrics and debugging tools, and collaborate with ML, product, and support teams to deliver robust, scalable conversational AI.

Lead design and implementation of agentic, conversational AI features for enterprise use cases. Collaborate with ML experts, PM, UX, and GTM to scope, deliver, and scale product-grade LLM/GAI solutions and expand platform reach.

Lead and grow engineering teams building distributed, agentic AI systems and frameworks. Drive architecture, scalability, reliability, and operational excellence across cloud-native, high-throughput services while partnering with cross-functional stakeholders.

Build and deliver production-ready, LLM-enabled full-stack applications: backend services, data/LLM pipelines, vector search, and front-end UIs. Embed with customers onsite to deploy, iterate, codify reusable AI assets, shape platform tooling, and ensure scalable, observable, secure enterprise deployments.

Build and productionize reliable, scalable agentic AI systems (orchestration, sandboxed execution, latency optimization, agent memory, self-reflection, knowledge graphs, multimodal I/O). Implement frontier AI algorithms, ship production-grade code, mentor engineers, collaborate with ML, security, product, and UX teams, and drive roadmap and reliability improvements.

Serve as the technical face of Platform and AI for solution sales: build POCs and accelerators, design agentic AI applications (multi-agent orchestration, RAG, prompt/context engineering), create reusable components, run discovery workshops and demos, advise on integrations, data pipelines, and security, and collaborate with sales, product, and services to scale regional capabilities.