Top AI Specialist Jobs in Los Angeles, CA

Design, build, test, deploy, monitor, and maintain production LLM-based agentic solutions for Commercial Customer Success. Integrate agents with CRMs and Samsara systems, define evaluation frameworks and success metrics, implement automated tests and monitoring, iterate on models and prompts, and demonstrate impact on customer outcomes and retention.

Deliver data modernization, analytics, and AI solutions on GCP: build data pipelines, optimize BigQuery, support ML/Agentic AI (Vertex AI, Gemini), implement MLOps, assist dashboards in Looker, gather requirements, and support data governance and security.

Teach an intensive course on cinematic AI, generative design, and emerging creative technologies to students in creative industries, focusing on practical applications and ethical considerations.

Design, implement, and maintain AI-driven workflow automations using Microsoft Power Automate and approved AI tools. Discover and document business processes, translate needs into requirements, coordinate custom NEXUS development with software teams, deliver training and documentation, monitor adoption and performance, and ensure Responsible AI and compliance practices across ISAT, CEAS, and Tomarco business units.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) for production LLM applications in regulated environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and cost optimization. Implement RAG, Agents, inference, guardrails, observability, access controls, and governance, with emphasis on Responsible AI and production reliability in financial services.

Design, build, and operate a secure, scalable enterprise Generative AI platform on AWS (including AWS Bedrock). Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and governance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Support production-grade GenAI applications in regulated/financial environments.

The role involves designing and delivering AI training programs, creating learning materials, and facilitating workshops to enhance user understanding of AI tools within enterprises.

Lead sales and deployment of custom AI/ML solutions, driving pipeline and revenue for allocated accounts. Collaborate with Field Sales, Product, Sales Engineering and AI teams to discover requirements, architect agentic AI solutions, write SOWs, negotiate commercial terms, and manage complex sales cycles to ensure customer adoption and measurable business outcomes.

Design, develop, and deploy Agentforce AI agents and custom actions on the Salesforce platform. Build Apex classes, LWCs, flows, and API integrations with Data Cloud and legacy federal systems. Enforce AI safety, federal security/compliance, support testing/UAT, and enable secure DevSecOps/CI/CD deployments in cleared environments.

Design, develop, and deploy Agentforce AI agents and custom actions on Salesforce. Build Apex, LWCs, flows, and secure API integrations with legacy federal systems and Data Cloud. Ensure AI safety, compliance, testing, and support CI/CD/DevSecOps practices in cleared federal environments.

Designs, builds, tests, and deploys AI-enabled automations and copilots for GTM and RevOps. Creates reusable agent templates, prompt libraries, and orchestration patterns; implements end-to-end API integrations; monitors performance; documents and hands off production solutions; and trains/coaches business teams on safe, responsible AI usage and prompting best practices.

The role involves cultivating technical relationships with Accenture, supporting solution development, customer deal support, and representing Databricks at events.

Lead design and implementation of AI and data governance frameworks, privacy guardrails, metadata standards, and compliance with GDPR/HIPAA/CCPA/NIST AI RMF. Monitor and audit models for bias, explainability, and transparency; partner with engineers, stewards, and leaders to embed ethical decision-making, set KPIs, run audits, and produce dashboards and reports to drive governance adoption.

Review machine-translated content into Finnish by comparing source and translation, making pass/fail quality judgments on accuracy, grammar, and naturalness. Follow guidelines and provide consistent assessments during a one-year, 1–5 hour/week freelance engagement.

Compare source texts with Hebrew machine translations to judge accuracy, grammar, and naturalness. Make simple pass/fail quality assessments following provided guidelines. Weekly commitment 1–5 hours for a year; no rewriting required.

Create, optimize, schedule, and publish blog and social content about AI applications. Test headlines, landing pages, and ads; review analytics, predict opens/clicks/conversions, write performance reports, and personalize curated content.

Design, build, and deploy prompt-engineered AI agents and copilots for sellers. Create and tune prompts, connect LLMs to GTM systems (Salesforce, Snowflake, Databricks), ship production workflows, run experiments, monitor performance, and drive field adoption while ensuring security, privacy, and responsible AI governance.

Design and maintain a skill and concept graph, build ML models to infer learner skills, and develop recommendation systems and LLM-driven features. Ship production-ready LLM systems, define explainability standards, partner with frontend and product teams, and monitor model performance and evaluation frameworks.

The AI Adoption Specialist guides organizations in integrating AI technologies, developing strategies, conducting pilots, and overseeing deployment while monitoring performance.

Design, build, and operate a secure, scalable Generative AI platform on AWS (including Bedrock) to support production LLM applications in regulated financial environments. Own platform lifecycle: architecture, deployment, operations, monitoring, incident management, reliability, and performance. Implement LLM inference, RAG, Agents, guardrails, observability, security controls, access management, compliance, and cost optimization. Provide production support, reliability engineering, and AI governance.

Define and maintain benchmark datasets and gold standards, create training and certification materials, monitor annotator drift, perform double-blind quality audits, and act as a high-trust annotator for critical production labeling. Collaborate with Computer Vision and Data Ops to improve the quality pipeline and scoring models.

Operate and troubleshoot GPU-based generative AI inference workflows for image, video, audio, and multimodal projects. Prepare and validate inputs, tune parameters, debug runs, maintain reproducible launch workflows, partner with researchers and creatives, own quality control, and improve tooling and automation for production-ready outputs.

Join an internal AI enablement team to assess workflows, build prompt-based automations and lightweight apps, coach business teams, test and document tools, track user skill development, research AI platforms, and ensure governance and security compliance.

The role involves designing and implementing automation systems, improving workflows, and developing tools for sales support using AI and automation platforms.

Design and implement high-fidelity spatial mapping and real-time object recognition pipelines. Integrate vision systems with robotic manipulation and navigation controls. Train and fine-tune Vision-Language-Action models and work with multimodal spatial AI frameworks and robotic hardware.