Top AI Jobs in Los Angeles, CA

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

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

Lead product-focused quantitative analyses and machine learning efforts to generate actionable insights, drive product decisions, and optimize features. Collaborate with cross-functional teams to design metrics, build scalable statistical solutions, create dashboards, and communicate findings while using AI tools responsibly.

As AI Enablement Services Lead, you will design AI solutions for operational tasks, automation of delivery processes, and enhance team capabilities in utilizing AI effectively.

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

Lead design, launch, and lifecycle management of Pluralsight solutions (AI, Cloud, Security). Define expert POV, build curricula, labs, assessments, and blended learning programs. Own roadmap, metrics, GTM partnership with Sales and Marketing, and continuous iteration using data and SME collaboration to drive enterprise customer outcomes.

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 product vision and strategy for an end-to-end AI-powered software factory. Integrate planning, coding, review, and verification across GitLab Duo Agent Platform and product areas. Collaborate with engineering, design, and GTM teams, identify gaps and dependencies, present recommendations to executives, and drive execution to deliver cohesive developer workflows.

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.

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.

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.

Design, build, deploy, and operate end-to-end human-centered agentic AI systems across frontend, backend, data, and intelligence components. Integrate AI/ML/NLP into workflows, implement agent behaviors, support sales with demos and POCs, create scalable APIs/services, and provide technical guidance for proposals and delivery.

The AI Corporate Strategy Director will lead the design and operations of the company as an AI product, integrating AI into its framework and decision-making processes while collaborating with leadership.

The AI Automation Engineer will automate internal processes, mentor non-technical staff on building tools, and ensure solutions deliver measurable business impact using AI technologies.

As a Staff Applied AI Scientist, you will design and deploy AI systems using LLMs, improve agent performance, and collaborate with engineering to enhance systems for customer impact.

Contractor will design, build, and deploy internal AI-enabled web applications and tools across frontend and backend stacks. Responsibilities include UI development, APIs, databases, LLM integrations, workflow automation, code review, security best practices, and collaborating with stakeholders to translate business needs into scalable, maintainable solutions.

The AI Operations Associate monitors AI-driven workflows, investigates incidents, supports operational controls, and recommends improvements to maintain workflow reliability and safety in finance environments.

Lead client engagements to assess business challenges, define enterprise data and AI strategies, develop roadmaps, guide solution design and delivery, provide technical leadership and mentoring, and support practice growth via presales and thought leadership.

Lead development and implementation of AI legal and compliance frameworks. Conduct cross-functional AI reviews, maintain governance docs (model cards, impact assessments), partner with engineering on transparency and fairness requirements, build incident response and monitoring processes, and scale AI legal review workflows.

Design and implement multi-step agentic AI workflows (orchestration, retrieval, tool use, state management) using frameworks like LangGraph/LangChain. Build retrieval pipelines over proprietary CRE data, evaluate and monitor model quality with human-in-the-loop processes, integrate Anthropic models on AWS Bedrock, implement guardrails and observability, and rapidly prototype features with Product and Design to deliver trustworthy, source-linked AI capabilities that perform real business actions.

Design, build, and operate production AI and data systems for marketing: LLM/agent orchestration, retrieval pipelines, data pipelines, CDP and warehouse architecture, automation of manual workflows, data quality and reliability, stakeholder collaboration, and mentoring. Ship production-grade Python and SQL solutions and evaluate/monitor AI systems.

Own the technical vision and architecture for an AI platform of agents, skills, and tools. Scale retrieval/knowledge systems, build developer experience, orchestration, observability, and evaluation/feedback loops. Align cross-division engineering strategy and drive platform adoption.

Develop and test AI-powered applications and internal tools using LLMs and AI APIs. Build prototypes, integrate AI services across web, mobile, and backend systems, participate in code reviews and sprints, and apply best practices in software engineering and generative AI.