Top Natural Language Processing (NLP) Jobs in Los Angeles, CA

Lead end-to-end performance of customer-facing conversational AI and knowledge base. Design, test, and optimize AI conversations, define intents and success metrics, analyze KPIs, maintain enterprise knowledge, run continuous improvement using analytics and experimentation, and partner cross-functionally to improve CX and business outcomes.

Design and implement scalable, secure inference services for speech processing. Optimize networking, audio transcoding, latency, memory, and distributed compute orchestration. Debug complex system issues, customize backend services for customers, and partner with Product to deliver end-to-end features.

Design and deliver LLM-powered, agentic AI systems to automate customer support and compliance. Build scalable, secure backend infrastructure in Python and Go, integrate third-party models/APIs, implement grounding and guardrails, and measure performance. Lead end-to-end projects, mentor engineers, conduct code reviews, and participate in on-call and incident response to improve resolution times and reduce operational costs.

Design, develop, and deploy machine learning and NLP solutions at scale. Work with cross-functional teams to build content classification, representation learning, search, and recommendation models using classical ML, deep learning, and LLMs. Process large datasets with Python, SQL, and Spark, and communicate results to stakeholders with clear documentation.

Assist the AI engineering team with NLP research, language model development, data annotation, experiments, and model evaluation. Support multilingual translation, content moderation, analytics, and other language-related features for a football-focused social and messaging platform.

Build, productionize, and operate AI-driven features and integrations across frontend, backend, and model layers. Prototype and deliver agent-driven experiences (conversational interfaces, RAG, tool-calling), integrate LLMs and external data sources, and collaborate with product and design. Participate in on-call/standby duties.

Record natural, conversational customer-service style speech from a home studio. Submit two audition samples; if selected, complete two supervised ~4-hour remote recording sessions meeting technical audio specs.

Reviews written content and AI-generated responses for accuracy, clarity, grammar, coherence, completeness, and guideline adherence. Provides concise, constructive feedback, identifies subtle linguistic errors, documents findings using evaluation tools, and consistently applies evaluation criteria during a four-week remote contract sprint requiring at least 20 hours per week.

Build and own conversational voice AI products end-to-end: architect, implement, and deploy the platform. Design infrastructure, develop front-end and back-end systems, deliver reliable customer outcomes, and collaborate directly with the CTO to scale the product for enterprise customers.

Work across AI, backend, and frontend: curate and clean writing datasets, fine-tune large language models, run training experiments, develop metrics and eval sets, build backend services in Python/Django, and implement frontend features with React.