Top AI & Machine Learning Jobs

Design, build, and operate agentic LLM-powered workflows, autonomous agents, and RAG/vector retrieval systems. Own end-to-end delivery including CI/CD, IaC, observability, DevSecOps, and Salesforce integrations to productionize enterprise AI for GTM applications.

Lead design and build of an AI-native marketing platform: integrations, multi-agent orchestration, UIs, tooling, analytics, CI/CD, auth/multi-tenancy, and production AI agents to automate marketing workflows and drive adoption across teams.

Build and scale CrowdStrike's internal Generative AI platform by designing cloud-native Golang services, operating secure LLM deployments, creating integrations and connectors, implementing high-performance document processing and RAG pipelines, owning features end-to-end, and supporting internal users and stakeholders.

Lead the Data and ML Platform team, defining vision and strategy, overseeing platform development, fostering innovation, and managing a distributed team.

The Manager of Data Science will lead a team focused on AI innovations utilizing LLMs, provide mentorship, and align technical strategies with business goals.

The role involves researching, designing, and prototyping generative AI solutions for cybersecurity. Responsibilities include building datasets, training models, and presenting findings to various audiences.

Design, build, and deploy production LLM-based agents from prototype to production. Lead prompt engineering, fine-tuning (LoRA/QLoRA), performance optimization, and scalable, secure deployments. Collaborate cross-functionally to integrate agents into enterprise workflows and ensure AI safety and responsible development.

The role involves deploying and supporting CrowdStrike's AI capabilities in cybersecurity, optimizing threat detection, and mentoring teams on AI solutions.

This role involves designing, building, and scaling a Data+ML platform, collaborating on machine learning pipelines, and incorporating cloud services for deployment and execution.

Lead design, deployment, and operationalization of agentic LLM-driven workflows across GTM systems. Translate business needs into scalable AI integrations, define orchestration and governance patterns, guide engineering teams, ensure security/compliance, and drive stakeholder alignment for enterprise AI programs.