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

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.

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 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.

Define and own the quality bar for Spotify's AI voice models. Design repeatable evaluation rubrics and run qualitative and MOS-style campaigns. Benchmark against competitors, synthesize findings, recommend improvements, and partner with voice, ML, product, and vendor teams to influence research and production priorities across languages and use cases.

Lead and grow a data science team to design, prototype, and productionize NLP/LLM systems for legal content. Set AI strategy, build evaluation and monitoring, drive RAG/agentic solutions, collaborate cross-functionally, and ensure scalable, reliable deployment and responsible use of generative AI.

Design, build, test, and deploy agentic, multi-step LLM-driven AI workflows for clinical operations and research. Integrate multimodal data, implement RAG/grounding, ensure reliability, traceability, and security, and collaborate with clinicians and engineers to deliver production-ready systems.

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.

The Senior Applied AI/ML Scientist will architect and implement AI modeling efforts, focusing on fine-tuning large language models, while handling data lifecycle and ensuring model reliability in production.

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.