Top AI Jobs in Los Angeles, CA

Develop data science solutions for payments across Square and Cash App. Build AI-powered tools, ETL pipelines, dashboards, machine learning models, experiments, and cloud data systems. Partner with Product, Engineering, Finance, and Operations to improve payment success, cost efficiency, risk mitigation, and decision-making. Translate business needs into practical solutions, research questions independently, and operationalize data processes and infrastructure.

Develop data tools, AI automations, ETL pipelines, dashboards, and machine learning models for payments. Analyze experiments, optimize payment performance and costs, mitigate risk, maintain data systems and cloud infrastructure, and translate business needs into actionable solutions while partnering with Product, Engineering, Finance, and Operations.

Build AI-powered workflows, agents, integrations, and internal tools that automate People Operations. Partner with People, Engineering, and IT to modernize onboarding and other employee processes, while implementing secure access controls, human oversight, escalation paths, and production-ready architectures. Prototype with users, iterate quickly, and measure improvements in efficiency, employee experience, and operational consistency.

Lead GitLab’s company-wide strategy for autonomous, agentic software development workflows. Identify and validate AI opportunities across the SDLC, build prototypes and reference architectures, establish evaluation frameworks and safety controls, and drive internal adoption. Partner across Engineering, Product, Infrastructure, Security, Architecture, and Data and ML teams to scale reliable, observable, compliant agentic capabilities into customer-facing products. Mentor senior technical leaders and represent GitLab externally on AI-assisted development and productivity measurement.

Build and operate secure, scalable AI infrastructure and cloud-native platforms across on-premises and cloud environments. Develop AI agents, MCP servers, microservices, automation, and Kubernetes-based workloads. Establish governance, security, observability, and operational standards for AI systems. Monitor infrastructure, troubleshoot production issues, improve processes, document runbooks, and support platform reliability while collaborating with artists, production teams, and engineers.

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.

Develop and implement AI solutions and machine learning systems that enhance products and solve complex client problems. Responsibilities include advanced analytics, LLM production deployment, prompt engineering, RAG pipeline optimization, cross-functional collaboration, technical discovery, responsible AI advocacy, client relationship building, and mentoring junior team members.

Leads and scales AI engineering teams responsible for production LLM systems, agents, integrations, and shared AI platforms. Oversees architecture, delivery, reliability, cost, latency, evaluation, observability, governance, security, and operational practices. Partners with product and business leaders to prioritize investments, manage dependencies, and establish reusable engineering standards. Develops engineering leaders and drives alignment across teams while ensuring safe, scalable AI adoption.

Lead Crunchyroll’s enterprise-wide AI Enablement function, setting strategy, priorities, operating models, governance, and adoption metrics. Identify and redesign workflows using AI, agents, and automation; translate business needs into scalable solutions; and partner with Engineering, Data, IT, and Enterprise Technology teams. Build AI fluency through learning programs, playbooks, and communities of practice. Manage external experts and vendors, lead a lean high-performing team, and report progress to the Executive Office.

Develop deep learning and 3D computer vision models for state estimation, visual navigation, localization, depth, correspondence, and pose estimation. Own data preparation, training, evaluation, benchmarking, and reproducible workflows. Integrate learned measurements into VIO and terrain-relative navigation systems, optimize models for onboard compute, and collaborate with deployment, software, systems, and flight-test teams to deliver production-ready Hivemind SDK components.

Leads and grows a perception AI engineering team building autonomous spacecraft capabilities, including synthetic data generation, multi-target tracking, sensor fusion, camera calibration, object detection, and edge deployment. Provides technical direction, defines validation standards, owns the team roadmap, coordinates cross-functional delivery, manages hiring and development, and ensures reliable performance under spacecraft compute, power, and operational constraints.

Leads Fusion’s Technical Architecture practice while personally building production AI and LLM tooling for Professional Services. Responsibilities include managing and mentoring architects, setting architecture standards, supporting enterprise presales and regulated customers, modernizing delivery infrastructure, establishing AI security guardrails, evaluating emerging AI capabilities, and driving adoption through training and enablement. The role requires deep Salesforce or ServiceNow expertise, hands-on software development, enterprise integration knowledge, and executive-level customer engagement.

Design, develop, test, debug, document, and deploy advanced AI/ML applications. Collaborate with AI/ML and software engineers to deliver solutions in development and production environments, develop software and testing requirements, and support rapid prototyping and demonstrations. The role involves LLMs, NLP, computer vision, sensor fusion, explainable AI, and responsible AI for advanced aerospace and national security systems.

Leads Unanet’s internal data strategy and architecture for enterprise AI. Defines the shared data foundation, target architecture, governance standards, roadmap, and reusable approaches for AI assistants, agents, and workflows. Evaluates platforms and integration options, validates technical solutions, and coordinates IT, Security, Legal, Engineering, business owners, and system specialists. Advises senior leaders, establishes data quality and stewardship requirements, and helps determine when data is ready to support scalable AI initiatives.

Design, build, deploy, and maintain resilient, scalable backend services and platform components for Toast's Voice AI platform. Lead cross-cutting architecture and projects, integrate AI platforms (LLMs), implement observability and evaluation for AI systems, set engineering standards, and mentor engineers.

Own the reliability and quality of an AI copilot for a trading platform. Build evaluation frameworks, benchmarks, quality gates, monitoring, incident response, and model improvement workflows. Partner with engineering and product to create safe, auditable tool interactions and improve assistant behavior. Develop domain expertise in trading, risk, margin, execution, and portfolio reasoning while operating across model, backend, and frontend systems.

Leads Utility’s AI practice by defining its roadmap, overseeing AI research and deployment, identifying client opportunities, mentoring AI teams, and establishing responsible AI practices. The role combines technical leadership, product strategy, client advisory, and operational execution across machine learning, generative AI, and intelligent automation initiatives.

Own production operations for workplace AI platforms, including configuration, integrations, observability, secrets, access controls, model and prompt changes, benchmarking, and incident response. Translate technical findings into governance, risk, compliance, and training materials while collaborating with Security, Legal, HR, and business stakeholders. Investigate failures, implement mitigations, document root causes, and maintain reliable, secure AI services.

Lead design and delivery of advanced data and ML solutions, performing exploratory analysis, statistical modeling, and visualization to inform strategy. Manage and coach teams, collaborate with clients to validate outcomes, and improve analytics processes and data quality to drive business decisions.

Lead and oversee multiple multidisciplinary teams to architect, develop, deploy, monitor, and maintain full-stack AI solutions (including LLM integrations). Provide strategic and technical leadership, drive experimentation and CI/CD practices, ensure quality and stakeholder alignment, promote innovation, and mentor senior and junior team members to deliver business-aligned AI outcomes.

Leads teams in designing and deploying scalable AI and machine learning solutions for consulting clients. Responsibilities include data wrangling, complex analysis, data modeling, AI system implementation, data pipeline and infrastructure oversight, deep learning, neural networks, data quality validation, and stakeholder collaboration. The manager coaches team members, manages performance, supports innovation, and applies Python, Java, and cloud technologies to build production-ready AI applications.

Lead AI engineering teams to design, build, and deploy end-to-end AI solutions. Manage client relationships, plan and deliver projects, mentor staff, drive adoption of cloud-native microservices, CI/CD, vector databases and orchestration tools, and ensure high standards of quality, innovation, and compliance.

Lead and coach teams to design, develop, and deliver production-grade AI and data solutions for clients. Manage client accounts, ensure quality and timelines, analyze complex datasets, implement best practices, and drive continuous improvement while fostering client relationships and technical excellence.

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.

Supports AI engineering initiatives at Vantor, contributing to spatial intelligence solutions and helping develop technologies that enable customers to understand current and future conditions. The posting provides limited role-specific responsibilities but emphasizes problem-solving, innovation, collaboration, and mission-focused work. Applicants must qualify as a U.S. Person under applicable export control and ITAR requirements.