Top AI & Machine Learning Jobs in Los Angeles, CA

As a Principal Data Engineer, you will design and implement LLM, AI-powered security data platforms, mentor engineers, and drive the adoption of data solutions across teams.

Lead and grow an AI Platform Enablement team to build a governed internal AI development environment. Define platform strategy, partner with security and infrastructure, drive adoption via enablement programs, and establish metrics for usage, onboarding, and control effectiveness. Act as an executive-facing leader delivering secure, scalable platforms and change management.

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.

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

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.

Lead hands-on engineering delivery of agentic AI solutions for GTM systems. Design and build LLM-powered workflows, autonomous agents, RAG and semantic search pipelines, Salesforce and Slack integrations, CI/CD and observability, enforce AI governance/security, mentor engineers, and drive prototypes to production across enterprise GTM platforms.

Lead product vision and roadmap for agentic AI across GTM applications. Partner with engineering, data, and business teams to identify AI opportunities in Lead-to-Cash and Customer Success, define epics/user stories, prioritize backlog, set AI KPIs, and drive adoption of LLMs, autonomous agents, and responsible AI practices to deliver automation-first GTM workflows.

Design, build, deploy, and iterate production-ready AI agents and LLM-based solutions that integrate with enterprise workflows. Rapidly prototype, evaluate, and optimize agents for performance, cost, and adoption. Partner across functions to redesign workflows, contribute to an AI Center of Excellence, and ensure responsible, secure, and scalable agent development.

Design, build, and operate large-scale LLM infrastructure and data platforms for training, fine-tuning, and inference. Provision GPU clusters, optimize GPU utilization, implement model lifecycle management, deploy inference frameworks, create evaluation and observability systems, and collaborate with data scientists to productionize AI capabilities. Mentor engineers and enforce MLOps/DataOps best practices.