natural-language-processing jobs in San Diego

Mid-level software engineer building AI/ML capabilities for a defense customer. You'll develop NLP and machine learning pipelines in Python (text analytics, topic modeling, embeddings, entity extraction), design knowledge graphs and network-analysis tools, develop collaborative TypeScript front-end applications, and deploy APIs and production systems.…See more Requires 4+ years Python development or equivalent front-end experience plus 2 years Python, hands-on NLP/ML experience, and ability to work with limited supervision.

Senior technical leader responsible for integrating AI/ML systems into secure, scalable DoD-compliant environments. Will architect AI system deployments, establish DevSecOps practices, ensure compliance with RMF/NIST 800-53/DISA STIG standards, and provide technical guidance across engineering teams.…See more Requires deep expertise in AI/ML production systems, containerization, CI/CD, and cybersecurity controls, with hands-on experience in Python, Kubernetes, and modern infrastructure tooling.

Lead a specialized team of software engineers at the intersection of hardware, software, and AI, focusing on developing innovative Pixel experiences using sensor signals. The role requires deep expertise in real-time embedded software development, sensor fusion algorithms, machine learning infrastructure optimization, and AI/ML design.…See more You will independently design and implement systems, collaborate with stakeholders on technical direction, and manage a team building power-efficient, sensor-driven features leveraging computer vision, signal processing, and estimation theory.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Senior Software Engineer at ServiceNow building enterprise-grade, AI-integrated conversational platforms and large-scale server-side systems. You'll design and implement highly interactive, performant applications; apply AI/ML concepts to enhance platform functionality; and write clean, scalable code following best practices in architecture, testing, and code review.…See more The role requires expertise in backend (Java, Spring, Hibernate, REST, SQL), frontend (JavaScript, Python), and machine learning/NLP systems including Large Language Models, with collaboration across product and engineering teams from design through delivery.

Lead a specialized team of software engineers developing innovative Pixel sensor experiences at the intersection of hardware, software, and AI. You will drive the design and implementation of real-time embedded systems that process sensor signals efficiently while applying machine-learning and signal-processing algorithms in a power-optimized manner.…See more Required: 8 years software development experience, 5 years in computer vision or signal processing, 5 years leading ML design and infrastructure optimization, and 3 years technical leadership. This role demands deep expertise in embedded software, AI/ML algorithms, sensor fusion, and the ability to independently architect systems while managing a team.

Join Qualcomm's Enterprise AI Engineering organization as a BizAI Tech Functional Engineer, bridging business stakeholders in Finance, Sales, and SCM with the AI engineering team. You will design and deliver AI-driven agents, natural-language analytics, and workflow automations on Qualcomm's unified BizAI platform, integrating with enterprise systems like Databricks, Oracle, Salesforce, and M365.…See more The role requires full-stack technical expertise (Python, TypeScript, FastAPI, n8n, Kubernetes) combined with functional fluency to translate process pain points into governed, production-grade solutions that meet SOX, security, and auditability standards. You'll support adoption through enablement and hands-on guidance while defining standards for scalability and compliance across the enterprise.