Top AI Jobs in Los Angeles, CA

The Senior Manager, Marketplace will scale the Metropolis Marketplace, manage B2C partnerships, and collaborate cross-functionally to drive growth and optimization.

The Account Executive is responsible for generating sales, maintaining relationships with clients and AWS, managing sales cycles, and promoting market growth.

As an Associate Technical Onboarding Manager, you will manage the onboarding process for new customers, gather technical requirements, and ensure quality customer experience through project management.

The Key Account Director, Data & AI Apps will expand client relationships with pharmaceutical companies, driving revenue through the use of Tempus' platform in precision medicine. Responsibilities include developing account strategy, maintaining executive relationships, negotiating contracts, and collaborating with cross-functional teams to deliver value.

As an AI Creative Technologist, you will architect AI-enhanced solutions, collaborate with various teams, and serve as the technical point of contact for partners, integrating LTX technologies into production pipelines.

As a Staff Product Manager, you'll drive the strategy and success of SIEM products, collaborating with various teams to fulfill customer needs and market demands while focusing on security for SMBs.

The AI Governance Manager at PwC will lead teams in assessing governance and risk frameworks, mentor junior staff, and enhance project delivery through innovative methodologies. The role involves maintaining compliance standards and building client relationships using advanced analytics and technology resources.

The Lead AI Product Engineer will design, build, and operate AI agent systems, focusing on architecture, reliability, and performance while collaborating on user-centric workflows.

Design and implement AI agents and Model Context Protocols to integrate enterprise systems (NetSuite, Zuora, Jira) with LLMs. Build secure, SOX-compliant automation and orchestration workflows, measure KPIs, and partner with Finance, IT, and Security to operationalize AI across enterprise applications.

The Director of Analytics & AI Solutions defines and executes product strategy for analytics and AI solutions to aid decision-making across Studio Distribution, collaborating closely with business and engineering teams.

As a Staff Product Designer at FloQast, lead design strategy for AI-driven product capabilities, mentor teams, and ensure design consistency across platforms while enhancing user experiences and stakeholder communication.

Develop and implement automation and technological solutions for production equipment in aerospace manufacturing, focusing on safety, process control, and productivity improvements.

Lead design and delivery of enterprise BI for Finance: architect Power BI solutions, build data models and dashboards, develop complex SQL transformations, ensure performance and governance, align stakeholders, and mentor teammates.

Lead multi-year strategy and delivery for Licensing Financial and AI ecosystems within Disney Consumer Products. Architect roadmaps, drive executive alignment, oversee end-to-end product development, prioritize portfolios, and manage global change adoption for AI/LLM-driven automation and integrated finance systems.

Design and implement AI models for robotic manufacturing, develop simulation tools, and ensure model transfer from simulation to reality while optimizing ML models in production.

Lead development of AI and ML solutions for healthcare systems, overseeing teams, driving use case development, and ensuring operational excellence while managing global delivery operations.

The role involves designing and operating real-time AI systems for sports analysis, integrating various data signals under tight constraints and mentoring other engineers.

As a Lead Product Manager, you'll drive AI-based consumer products from concept to commercialization, managing strategy, execution, and P&L while collaborating with cross-functional teams.

Lead CrowdStrike's marketing transformation by operationalizing AI-enabled workflows, driving adoption and governance of agentic systems, defining role and skill evolution, shaping product roadmap, measuring impact, and managing change to embed new ways of working across marketing teams.

Design, build, deploy, and maintain scalable, resilient backend services for a Voice AI platform. Lead cross-cutting projects, make architectural decisions, integrate AI platforms, implement observability and evaluation frameworks, and mentor engineers.

Lead design and implementation of agentic AI workflows and integrations for Acquia DAM. Build, ship, and observe production AI features (auto-tagging, search, governance), set AI engineering standards, evaluate models and tooling, mentor engineers, and represent AI architecture to product and customers.

Evaluate and validate AI Coach chat outputs for accuracy and risk, act as subject-matter expert in personal financial planning, identify enhancements, escalate issues to Ops/Product/Compliance, and contribute reusable solution libraries to improve member experience.

Take Deepgram's speech models and optimize, compile, and run them on resource-constrained embedded and edge hardware. Work across model compression, runtime performance (C/C++/Rust), RTOS/bare-metal and embedded Linux environments, vendor NPUs/DSPs and inference runtimes, benchmarking, deployment pipelines, OTA updates, and partner with silicon vendors to enable real-time, low-power on-device voice experiences.

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.

Lead end-to-end development of full-stack AI features on a Ruby on Rails backend and React frontend. Build and optimize AI infrastructure for production LLM inference, implement RAG and AI agents, design and run experiments and A/B tests, improve tooling and processes for scale, collaborate with designers and leaders, and iterate quickly while maintaining high code quality and user experience.