Top AI Jobs in Los Angeles, CA

Serve as a global SME for Industrial Metaverse technologies (PLCs, IoT, cloud/edge, digital twins, AI, EMC/RED, cybersecurity). Lead standards work, develop test programs, perform and supervise complex testing, train staff, represent UL externally, and support clients and continuous improvement across regional or global labs.

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.

Lead and operationalize GitLab's Internal Audit function: plan and execute risk-based audits, oversee SOX testing, facilitate enterprise risk management, coach a distributed audit team, implement QA/improvement programs, and report to senior leadership and the Audit Committee.

Lead design and implementation of Microsoft Dynamics 365 solutions, supervise and mentor teams, manage project delivery, translate complex requirements into technical designs, handle data migrations and integrations, and build strong client relationships while improving service delivery.

Design and deliver generative AI and computer vision models and on-device inference for consumer AR experiences. Prototype research advances, optimize models (compression, quantization, distillation), collaborate across teams, and productionize scalable inference pipelines for mobile and wearable platforms.

Design, build, and optimize scalable PySpark ETL pipelines and integrations (FiveTran, Plaid, APIs). Maintain production ML/LLM pipelines, monitor performance, automate testing, implement CDC and indexing for scale, and collaborate with stakeholders to integrate AI and big-data technologies.

As a Senior AI Engineer, you'll design and implement AI-powered automation tools, maintain LLM-based systems, ensure data quality, and enhance business processes through AI solutions.

Lead the identification, governance, development, deployment, and scaling of AI solutions for Appeals. Drive AI strategy, design and optimize AI agents, ensure governance and regulatory compliance, coordinate cross-functional teams, manage change and adoption, and measure outcomes to improve quality, efficiency, and user experience.

Lead design and prototyping of AI-enabled solutions for Oncology R&D. Develop data pipelines, feature engineering, analytics, and ML models on healthcare data. Partner with scientific and product teams to deliver usable tools, emphasize rapid iteration and production-readiness, and contribute to engineering standards and documentation.

Design and deliver end-to-end AI/ML solutions for Oncology R&D, working with multimodal datasets. Partner with scientists and product leaders to prototype, iterate, and deploy decision-relevant models, document methods for transparency, and ensure solutions are scientifically grounded and usable.

Lead product strategy and commercialization for AI-focused software within Internal Firm Services. Drive innovation, market and competitive analysis, TAM assessment, go-to-market planning, and portfolio management. Set strategic direction, maintain executive client relationships, mentor teams, and validate revenue potential to support investment and commercialization decisions.

Lead Oncology AI product strategy and a cross-functional AI engineering team to translate scientific needs into scalable AI solutions across discovery, clinical development, and real-world evidence. Define roadmaps, governance, success metrics, stakeholder engagement, and adoption to move AI initiatives from pilots to sustained impact.

The Software Engineer II will develop AI capabilities, implement workflows, manage integrations with LLM providers, and enhance the TrakSYS platform while ensuring security and reliability.

Lead technical execution and architecture for data-centric solutions: acquire, harmonize, store, process, analyze, and disseminate sensor/telemetry data. Serve as thread lead/Product Owner, define enterprise strategy, govern data standards, collaborate with stakeholders, and support risk mitigation and roadmap alignment. On-site role requiring active Top Secret clearance and SAP access.

Lead technical strategy and architecture for data-centric solutions across programs. Oversee data acquisition, harmonization, processing, storage, analysis, dissemination, and product lifecycle. Serve as technical lead/Product Owner, define enterprise data standards, decompose backlogs, prioritize features, advise leadership on analytics opportunities, and ensure mission-focused delivery within high-clearance environments.

Provide legal support for supply chain by drafting, negotiating, and overseeing commercial and government contracts; design policies, templates, and training; advise on FAR/DFARS flow-downs, proposals, and compliance; serve as primary legal contact for stakeholders and external parties; help scale legal processes across the company.

Perform systems engineering for aerospace products including MBSE modeling and simulation, requirements definition and verification, design analyses, documentation, root-cause investigations, cross-functional IPT support, and compliance with aerospace standards to meet schedule, cost, quality, producibility, and reliability targets.

Lead architecture and development of scalable full-stack applications and distributed backend services (TypeScript/React/Node/GraphQL). Drive technical strategy, cross-functional collaboration with manufacturing, robotics, and operations teams, establish engineering best practices, mentor engineers, and deliver production-grade, reliable, observable software for factory and manufacturing platforms.

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.

Develop and deploy machine learning systems for Mars missions, enhance atmospheric modeling, and integrate multi-modal data for autonomous science.

Build and maintain AI platform infrastructure, connectors, API integrations, and custom AI-powered applications. Implement authentication, data pipelines, and tooling to embed LLM capabilities across teams. Contribute code, documentation, reviews, and enablement while ensuring security and compliance for government requirements.

The role involves developing machine learning systems for Mars atmospheric modeling and multi-modal data fusion, contributing to autonomous science in space missions.

Build and lead an enterprise AI platform: design infrastructure, integrations, and custom AI applications. Own provider/tool selection, deploy production model pipelines and connectors, ensure compliance with government security requirements, mentor engineers, and deliver company-wide AI enablement and training.

Build and operate an enterprise AI platform and integrations that connect LLMs to internal systems. Develop production AI applications, manage model/provider evaluations, ensure security/compliance for government environments, and deliver company-wide AI training and enablement.

Develop physics-informed AI surrogates and surrogate modeling workflows for CFD, FEA, thermal and multi-physics simulations. Create scripted simulation models to generate training data, research new physics-AI methods (PINNs, neural operators, digital twins), integrate surrogates into engineering design, support government and internal R&D projects, and collaborate with cross-functional teams to transition models into engineering workflows.