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

Leads automated scoring and natural language application research for educational assessment products. Responsibilities include setting team priorities, mentoring scientists, designing and analyzing studies, developing machine learning applications, collaborating with stakeholders, presenting technical findings, writing reports, publishing applied research, and supporting products involving automated scoring, crisis-content detection, and formative feedback.

As a Research Engineer, you'll develop and manage data systems for text-to-speech projects and enhance machine learning models using innovative strategies.

Lead research and engineering work on LLM-based architectures for dialog, search, and destination entry. Optimize LLMs via prompting and fine-tuning, integrate them with ASR, TTS, and vision systems, and collaborate cross-functionally to deliver performant, resource-constrained solutions for automotive voice assistants.

Participate in a one-time, remote guided English voice recording session (~20 minutes) using your own compatible device. Must follow recording instructions, complete session in a quiet indoor environment, be at least 18, reside and record from an approved U.S. state, and submit one participation only. Approved participants who meet quality standards receive $25.

Lead design and validation of AI-driven legal product capabilities: develop NLP/LLM and generative AI solutions (RAG, prompts), design agentic workflows, build retrieval/hybrid search strategies with embeddings and vector DBs, analyze large legal datasets, establish model evaluation best practices, translate results into product recommendations, collaborate with product and engineering, and mentor junior team members.

Build and productionize large-scale TTS and adjacent speech models end-to-end: model architecture, training, alignment, evaluation, data curation, distributed GPU scaling, latency/cost profiling, tooling, and safety/mitigation for speech systems.

The role involves ensuring linguistic quality in TTS systems for Spanish by conducting phonetic analysis, developing lexicons, and collaborating with engineers and researchers.

Design and implement AI/NLP solutions to automate insurance policy administration (issuance, endorsements, renewals). Translate policy language into models and rule engines, integrate with PAS, ensure regulatory compliance, monitor model performance, and support underwriting, operations, and exception handling.

The Senior AI/ML Engineer will design, develop, and deploy language models for African languages, focusing on NLP applications and cultural context.

Perform language- and culture-sensitive human review and annotation of AI outputs across text, audio, and video. Generate or assess content, identify errors and cultural mismatches, provide structured annotations, and follow evaluation guidelines and QA calibration to improve models.