llm-large-language-models jobs in San Diego

As a Machine Learning Engineer at Qualcomm, you will design, develop, and deploy AI and Generative AI solutions for the Nimbus product line, focusing on network optimization, Digital Twin technologies, and LLM-based applications. You will collaborate with cross-functional engineering, product, and domain teams to translate business requirements into production-ready AI-enabled solutions, staying current with emerging AI technologies and best practices.…See more The role requires hands-on experience with model development, evaluation, deployment, and operationalization, along with strong software engineering practices for scalable and maintainable systems. You must communicate technical concepts effectively to both technical and non-technical audiences.

Staff or Senior Staff Software Engineer role leading design and development of Qualcomm's AI Stack (QAIRT/Genie) to enable efficient execution of generative AI models and large language models on low-power Snapdragon platforms. Responsibilities include developing core runtime components for resource-constrained inference systems, optimizing performance/accuracy/power consumption, debugging complex issues, and mentoring junior engineers.…See more Requires 5–8+ years of software development experience with strong C/C++ and Linux proficiency, plus knowledge of hardware acceleration and embedded AI deployment.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. The engineer will lead the technical roadmap for agent management—from provisioning and orchestration to compliance and retirement—while ensuring AI agents are secure by design with built-in visibility and guardrails.…See more The role requires 8+ years of software architecture and backend systems experience, deep knowledge of autonomous agent frameworks (LangChain, AutoGen, CrewAI), and expertise in cloud infrastructure (AWS, Azure, GCP) and Kubernetes. You'll collaborate cross-functionally with researchers, platform engineers, and product teams to bring agentic AI capabilities to production while establishing best practices for agent safety, observability, and ethical deployment.

As an Applied AI & Optimization Engineer, you will own optimization algorithms and ML systems for a manufacturing intelligence platform spanning planning, simulation, and AI assistance. You'll design scheduling and resource-allocation solvers, build analytics layers for operational intelligence, and lead LLM integration for both cloud and air-gapped DoD deployments.…See more The role requires 5+ years shipping production optimization or ML systems, deep Python proficiency, hands-on experience with MILP/constraint solvers or OR-Tools, and strong applied math skills in combinatorial optimization and statistical modeling.

Design, build, test, and operate production ML and LLM-powered components for cybersecurity applications at scale. You will turn ambiguous requirements into working code, partner across product and security teams, and apply AI safety and guardrail practices.…See more The role requires solid software engineering fundamentals, hands-on experience building production ML/LLM applications (RAG, embeddings, agents), and the ability to take prototypes to reliable, maintainable systems. You'll work with distributed systems, cloud-native technologies, and graph/data plumbing while contributing to code reviews and raising team quality standards.

The AI Engineer designs, builds, and operates production-grade AI solutions in Azure Government (GCCH) environments, with a focus on LLM and RAG implementations. Responsibilities include testing and optimizing LLMs and model variants, benchmarking RAG systems, building MCP server integrations to connect AI agents to enterprise data, implementing agentic AI workflows using platforms like N8N and Copilot Studio, and developing modular AI microservices.…See more The role also involves supporting security practices (RBAC, Key Vault, data protection), monitoring and incident response for AI workloads, and helping BI and DevOps teams adopt AI capabilities toward production. A Bachelor's degree in Computer Science or related field and 1–2 years' experience with LLMs, RAG, or AI solution development are required.

The AI Engineer designs, builds, and operates production-grade AI solutions in Azure Government environments, focusing on LLM and RAG implementations, agentic AI workflows, and secure enterprise integrations. Responsibilities include testing and optimizing language models, benchmarking RAG systems, building MCP server integrations, implementing multi-step AI agents using platforms like N8N and Copilot Studio, and developing modular AI microservices.…See more The role requires hands-on support for security (RBAC, Key Vault, data protection), monitoring, and incident response in Azure Gov, with a focus on moving proofs of concept toward production deployment.

Staff Engineer or Architect role focused on building and orchestrating AI agents in a compliance-heavy, globally regulated environment. You will troubleshoot novel failures across models, tools, and infrastructure; set technical vision; and leverage LLMs, RAG, tool use, and agent frameworks (LangGraph, CrewAI, AutoGen) in production systems.…See more Requires 8+ years of software engineering experience, hands-on LLM and agent-framework work, end-to-end ownership, and demonstrated ability to use AI agents effectively in your own workflow while maintaining accountability and clear mental models of system behavior.

The Enterprise AI FinOps Lead establishes financial governance for company-wide AI usage across multi-cloud (Azure, AWS, GCP), SaaS, and on-premise environments. The role owns cost visibility, show-back, optimization, budgeting, forecasting, and stakeholder engagement, with deep responsibility for AI-specific cost drivers such as tokens, models, prompts, embeddings, and RAG systems.…See more The leader translates telemetry into actionable insights, optimization programs, and executive reporting while managing the full departmental budget. This is a hands-on operator role requiring 8+ years in FinOps, cloud cost management, or enterprise finance, with strong analytical, stakeholder management, and executive communication skills.

Staff Inbound Product Manager for ServiceNow University, responsible for defining and executing product strategy across AI-powered learning experiences. The role involves leading product discovery across personalization, conversational AI, recommendations, and search capabilities; partnering with Engineering, Architecture, and Design to deliver enterprise-grade features; and translating learner and business needs into technical requirements.…See more Requires 8+ years of product/technical product management experience with strong expertise in enterprise platforms, AI technologies (LLMs, agents, conversational systems), and complex system integration.

Design and architect AI/ML platforms optimized for Qualcomm's hardware (GPU/NPU) and software stack, with focus on end-to-end performance analysis, algorithm tuning, and system bottleneck reduction. Analyze ML workloads across Computer Vision, Audio, Generative AI, and Agentic AI domains; correlate device performance against pre-silicon predictions; and develop reference implementations and tools for third-party developers.…See more Requires 15+ years in high-performance computing systems engineering or software with 5+ years in AI system optimization, strong expertise in AI frameworks and performance profiling, and ability to lead cross-functional teams and articulate complex technical concepts.

Qualcomm seeks a Machine Learning Engineer to design, develop, and deploy generative AI solutions focused on Large Language Models, Retrieval-Augmented Generation (RAG), and intelligent agent systems. The role involves implementing RAG-based solutions, optimizing LLM fine-tuning strategies, building evaluation frameworks, and maintaining agentic workflows for autonomous AI systems.…See more The candidate must have strong Python programming skills, practical LLM deployment experience, and familiarity with ML frameworks like PyTorch and TensorFlow, alongside knowledge of vector databases, cloud platforms (AWS, GCP, Azure), and modern MLOps infrastructure.

Software engineer developing oncology applications that integrate laboratory systems, data pipelines, and enterprise platforms. The role requires building AI-enabled capabilities (information retrieval, NLP extraction, summarization), deploying on Lilly cloud infrastructure, and owning application reliability and lifecycle.…See more Requires 4+ years of software engineering experience with BS/MS in computer science or related field; strong Python or modern server-side language skills, web frameworks (Django, Flask, Rails), front-end development, cloud deployment (AWS preferred), CI/CD, containerization, and familiarity with LLM APIs and agentic patterns are preferred.

As an LLM Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized software for AI model deployment (kernels, compilers, model efficiency tools), and lead ML technique application into products.…See more You will work independently with minimal supervision while providing technical guidance to team members and collaborating across cross-functional teams on joint hardware-software design.

Lead engineering and data science roadmap for Teradata's AI Platform, overseeing architecture, LLM integrations, RAG pipelines, vector store implementations, and data science experimentation frameworks. Partner with product, research, and engineering teams to define requirements for predictive modeling, multi-agent collaboration, and tool orchestration.…See more Manage and mentor a team of backend engineers, data scientists, and AI platform specialists while driving technical excellence, cloud-native practices, and platform scalability.

Sr. Staff IT Enterprise Architect will define integration standards and architectural decision frameworks across AppFolio's platforms (MuleSoft, AWS, Workato), promoting API-first and event-driven design.…See more The role partners with engineering teams to advance observability, reliability, and modern integration practices, while advising on AI-enabled capabilities and emerging technologies. Requires 10+ years of software engineering or integration architecture leadership with 8+ years designing enterprise integration solutions, hands-on platform experience, and demonstrated ability to influence across cross-functional teams without direct authority.

Build and deploy production-grade AI models that power Petco's e-commerce platform, including personalized recommendations, demand forecasting, and price optimization. Design and maintain robust MLOps pipelines for automated model retraining, monitoring, and 24/7 reliability across web and mobile.…See more Partner with Software Engineering and Mobile teams to integrate AI features into production systems, and mentor junior engineers on ML engineering best practices. Experiment with emerging technologies like Generative AI and LLMs to drive business impact.

Software engineer to update and enhance tactical network software for Navy C4I systems (ADNS, CANES, ISNS), including design, coding, implementation, and testing of afloat and ashore network applications. Responsibilities include integration of hardware/software systems, DevSecOps support, installation/load management, and test automation across development through production environments.…See more Requires a BS in Computer Science or related field with 3 years of software engineering experience and an active DoD Secret clearance with ability to obtain TS/SCI.

AppFolio is hiring a Staff Machine Learning Engineer to design, build, and operate their ML platform on AWS, supporting training, fine-tuning, inference, RAG, and cost optimization across the organization's AI initiatives. You'll partner with applied AI and research teams to productionize prototypes, maintain multi-provider LLM reliability (OpenAI, Google, Anthropic), and operate AI safety guardrails and authorization layers.…See more The role requires production-scale ML infrastructure experience on AWS (ECS, SageMaker, GPU fleets), deep knowledge of model serving and inference optimization, hands-on language model training, and demonstrated cost discipline across AI workloads.

Software engineer with 6+ years of backend development experience (or 4+ with a Master's degree) designing and optimizing high-performance algorithms for radar, optical, and infrared sensor systems. You'll work with a cross-disciplinary team to engineer scalable distributed systems, accelerate code on GPUs using CUDA, and integrate scientific codebases in Linux/Unix environments.…See more Strong expertise in C/C++, high-performance computing, MPI, parallel/distributed processing, and AI/ML algorithms is required, along with advanced mathematics or physics foundations and proven system-level problem-solving ability.

Senior AI Engineer building AI-powered learning systems for Shield AI's Hivemind autonomy platform. The role involves developing an AI training coach for context-aware guidance, creating tooling to generate technical workshops and curricula from learning objectives, and partnering with autonomy experts to produce assessments and labs.…See more Success is measured by shipped learning products, reduced time to technical proficiency, and demonstrated improvement in customer capability and product adoption.

This role combines pre-sales engineering with hands-on AI/automation expertise. You'll design and deliver technical presentations, build proof-of-value projects and custom dashboards for enterprise clients, and assist with RFPs—all while staying current on ClickUp's product roadmap.…See more You need 6+ years in customer-facing technical roles, demonstrated success with agentic AI workflows and integration platforms, and the ability to influence both technical and executive stakeholders toward adoption.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.

Design and build AI agents and full-stack web applications that automate enterprise workflows, with expertise in agentic AI frameworks, LLM orchestration, and generative AI integration. Architect a multi-agent platform enabling PM and engineering agents to exchange plans and context, while developing backend services in C#/.NET/Python/TypeScript and modern Angular/React frontends that connect to enterprise systems like Jira, Microsoft 365, and SQL/NoSQL databases.…See more Define agentic engineering standards including tool contracts, prompt management, guardrails, and agent evaluation. Requires hands-on experience with LLM application development, RAG, tool calling, prompt engineering, agentic runtimes (LangGraph, AutoGen, n8n), and full-stack enterprise application development on AWS or Azure.

Design and build AI agents that automate workflows within a multi-agent platform, enabling PM and engineering agents to exchange plans and context over shared program data. Develop full-stack web applications with generative AI functionality—conversational interfaces, natural-language querying, automated summarization, and in-context recommendations—using C#, .NET, Python, TypeScript, Angular/React, and integrations with Jira, Microsoft 365, Confluence, and SQL/NoSQL stores.…See more Define agentic engineering standards including tool contracts, MCP servers, prompt management, memory, guardrails, human-in-the-loop approval, and evaluation harnesses. Requires hands-on experience with LLM application development, agentic runtimes like LangGraph or AutoGen, full-stack enterprise development, and cloud deployment on AWS or Azure.