llms jobs in San Diego

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.

Lead end-to-end AI platform architecture and infrastructure at enterprise scale, designing and implementing generative AI capabilities including LLMs, RAG systems, and agentic AI with a focus on model serving, inference optimization, and production deployment. Establish MLOps/LLMOps best practices, build automated CI/CD pipelines tailored for AI/ML applications, and architect vector database integration and cloud AI/ML services.…See more Mentor engineering teams, drive cross-functional collaboration between software, product, and data teams, and continuously evaluate and optimize AI platform performance, scalability, and reliability.

Lead a machine learning engineering team designing Visual Language Action Models, Vision Language Models, and Large Language Models for autonomous driving and infotainment on Qualcomm's Snapdragon Ride platform. Optimize deep networks for accuracy-latency trade-offs on resource-constrained edge devices, focusing on low-level perception, end-to-end autonomous driving (L2/L3 ADAS), and multi-modal sensor fusion.…See more Drive cross-functional collaboration with automotive OEMs and internal Qualcomm teams while building a world-class AI/deep learning engineering organization. Requires 6–8+ years of systems engineering or machine learning experience (depending on degree level), with hands-on expertise in deep learning network design, quantization, and deployment on edge AI accelerators.

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.

Systems Engineer role supporting Navy C4I systems integration and sustainment across shore and shipboard environments. Responsibilities include network engineering verification (IDPs, schematics, CAD drawings), Information Assurance integration, DevSecOps engineering, proactive sustainment monitoring with predictive modeling, and coordination of pilot tests and global on-site technical activities.…See more Requires Bachelor's in Engineering with 3–7 years of systems engineering experience (depending on level), active DoD Secret clearance with ability to obtain TS/SCI, and proficiency in CAD tools (AutoCAD), network systems, and full development cycle management.

As a Senior AI Engineer at Teradata, you will design and build agent-based AI solutions that enhance developer productivity, working on AI agents and platforms across the Software Development Lifecycle. You'll develop scalable, reliable systems with strong proficiency in backend technologies (Java, Go, Python), design RESTful APIs, work with SQL/NoSQL databases, and apply AI/ML technologies including agentic AI and LLMs.…See more The role requires 5+ years of experience in backend services, distributed systems, or data platform development, with hands-on expertise in Kubernetes, containerization, and cloud platforms. You will collaborate with cross-functional teams, mentor engineers, and stay current with emerging AI/ML and cloud-native technologies.

The AI SW Integration Engineer will develop backend tools and services that automate test generation, improve requirements traceability, and streamline engineering workflows across teams. The role requires strong expertise in generative AI and large language models (LLMs), with hands-on experience designing and deploying agentic AI systems end-to-end.…See more You will integrate tools and databases via REST APIs, parse structured documents, and build automation solutions using Python and CI/CD pipelines. The ideal candidate brings 3–5 years of production experience developing automation or integration tools, plus familiarity with RAG, MCP, and requirements management workflows.

A senior full-stack engineer at Telesis Bio will design and maintain Python-based microservices using FastAPI and Docker, lead the architectural migration from Django REST Framework to FastAPI, and help transition the frontend from React to Python-native, server-driven UI patterns (Datastar/HTMX). The role requires deep full-stack Python proficiency, experience integrating LLMs and AI APIs into production, and the autonomy to take loosely defined problems, frame them clearly, and drive technical decisions across backend services and frontend interfaces.…See more You'll work hands-on with REST APIs, relational databases (PostgreSQL), TDD, CI/CD, and Docker while collaborating with cross-functional stakeholders and less senior engineers in an Agile Scrum environment.

Develop, optimize, and validate AI/ML solutions that leverage Qualcomm's AI inference accelerators for data center and hybrid applications. Design and implement GenAI and LLM applications, perform model benchmarking, optimize deployment strategies, and drive system-level architecture decisions.…See more Apply deep expertise in ML frameworks, system performance profiling, and parallel computing to ensure best-in-class inference performance, power efficiency, and scalability across heterogeneous hardware.

Mid-level full-stack software engineer responsible for developing, deploying, and troubleshooting distributed applications across application, OS, networking, and hardware layers. Must have 5+ years of professional experience with Python, modern front-end frameworks, RESTful APIs, Linux (RHEL preferred), containerization (Podman/OCI), Ansible automation, and Git.…See more Role emphasizes independent ownership of features from requirements through testing, strong debugging across system and software components, and integration with external systems and hardware interfaces.

Lead the design, development, and support of enterprise automation solutions across the Microsoft ecosystem, including Microsoft Intune, Microsoft 365, Entra ID, Azure Automation, Power Platform, Copilot Studio, and Azure AI. The role requires deep expertise in Microsoft cloud technologies and hands-on experience building scalable automation solutions using PowerShell, Azure Functions, Logic Apps, Microsoft Graph API, and AI-driven workflows.…See more Responsibilities include endpoint management, Microsoft 365 administration automation, Power Automate/Power Apps design, Azure AI integration, and operational reporting. The ideal candidate has 5+ years of enterprise Microsoft cloud experience and a passion for reducing manual effort through intelligent, secure automation.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. You'll lead the technical roadmap for agent management—from discovery and provisioning through task orchestration—while ensuring safety, compliance, and governance by design.…See more Working cross-functionally with product, platform, and research teams, you'll build foundational infrastructure for multi-agent collaboration, memory management, and extensibility, driving adoption across the enterprise. The role requires 8+ years in software architecture, backend systems, and Kubernetes/AI infrastructure, with deep expertise in LLM frameworks (LangChain, AutoGen, CrewAI), cloud platforms (AWS, Azure, GCP), and identity/access control patterns.

Qualcomm seeks a Staff Machine Learning Engineer to design and deploy AI/ML-based automation solutions for automotive cybersecurity and functional safety engineering workflows. The role involves building intelligent systems for document understanding, compliance automation, and engineering productivity, leveraging LLMs, GenAI, and agentic AI frameworks.…See more You will develop scalable end-to-end automation pipelines, contribute to knowledge systems and RAG platforms, and apply ML to security analysis and process optimization across the full product development lifecycle. The ideal candidate has 5+ years of ML/AI experience, strong programming skills in Python or C++, and familiarity with automotive cybersecurity standards such as ISO/SAE 21434.

As a Senior Software Engineer focused on AI Tools, you will reauthor and optimize generative AI models (LLMs like Llama, Phi, Qwen, and multimodal models) for efficient execution on Qualcomm's on-device hardware. You'll translate hardware constraints into model-level transformations that preserve accuracy while enabling edge deployment, integrate inference acceleration techniques, and collaborate with compiler and quantization teams to move research prototypes into production.…See more The role requires deep implementation-level knowledge of generative AI architectures, strong Python proficiency in large typed codebases, and hands-on experience optimizing inference for resource-constrained environments.

Principal Engineer leading the technical direction for ServiceNow's Conversational Analytics platform, which enables customers to query data in natural language using AI. The role combines hands-on architecture and prototyping with mentorship of engineering teams, requiring deep expertise in AI/ML systems, vector retrieval, agentic architectures, and knowledge graphs.…See more You'll collaborate with product and leadership to design cloud-based solutions integrating LLMs and AI into enterprise workflows, with accountability for customer success metrics and evaluation frameworks.