Top AI Automation Jobs in Los Angeles, CA

The AI Automation Intern will design and deploy AI automations, build tools, evaluate AI models, and create dashboards while working directly with the founding partner.

The AI Engineer will develop scalable AI systems, automate workflows, and collaborate with business teams to enhance operational efficiency across OpenSesame.

Lead execution of Product Engineering AI and automation initiatives across photonics products. Build and deploy reusable AI/automation tools, transform engineering data into AI-ready systems, and drive cross-functional adoption to improve development, qualification, manufacturing, and reliability processes.

The AI Automation Engineer will apply AI in finance operations to automate processes like AP, AR, and reconciliation, ensuring compliance and performance measurement.

Build scalable QC systems and validation pipelines for RL training data: define quality standards, design metrics and experiments, audit supplier datasets, partner with vendors to diagnose failures, and integrate learnings into infrastructure and vendor tooling.

The Director of AI Automation leads AI-driven automation systems, translating strategic goals into practical solutions, managing teams, and enhancing operational efficiency.

Join a talent pool to teach, author, or advise on AI-powered automation. Deliver live workshops, create course materials, design exercises, shape curriculum, review technical content, and support program updates. Part-time (10–15 hrs/week), remote with collaboration in European time zones. Roles span junior to senior levels and emphasize hands-on experience with automation platforms and real-world operational workflows.

The AI Automation Engineer develops AI-driven systems to automate sales and marketing workflows, partnering with various teams to enhance revenue generation and process efficiency.

Design and implement AI-native workflow orchestration and automation systems for legal services. Build integrations between AI models, CRMs, document systems, client portals, and internal tools. Develop agent workflows, vector retrieval and observability pipelines, monitor reliability and performance, troubleshoot integrations, and support governance, compliance, and scalable client experiences.

Develop and maintain an AI-driven pipeline to auto-generate, process, and publish real-life and digital quests. Integrate AI frameworks, design scalable automation workflows, analyze user data to improve generation quality, build API integrations, participate in architecture and documentation, test with pytest/unittest, and collaborate with cross-functional teams to validate LLM outputs against real-world data.

Design, build, test, and deploy AI agents, agentic workflows, and automation solutions. Partner with stakeholders to prototype and productionize full-stack AI applications across cloud, VPS, and local GPU environments while ensuring scalability, security, and performance.