llm-large-language-models jobs in San Diego

Senior Microsoft Forward Deployed Engineer who will design, build, and deploy GenAI/LLM-powered solutions for government clients, translating business problems into production-grade AI systems. The role requires 7+ years of software/data engineering experience, 1+ years hands-on with GenAI/LLM solutions, and deep expertise in Microsoft Azure (AI Foundry, OpenAI, AI Search), Python/TypeScript/C#, and Copilot extensibility.…See more You will lead project workstreams, work directly with client technical teams in fast-paced environments, and mentor others while building reliable, maintainable, well-documented code. 50% travel required.

The AI Architect II is a senior technical leadership role responsible for establishing architectural standards and patterns for AI solutions, including RAG pipelines, agentic workflows, and model serving. The role involves designing scalable AWS cloud architectures, defining MLOps practices, implementing responsible AI governance, and translating business requirements into enterprise AI and cloud strategies.…See more The position requires hands-on technical expertise to evaluate and integrate AI/ML services, lead systems design across microservices and event-driven architectures, and mentor engineering teams on cloud and AI best practices. This role drives technology decisions with real business impact while modernizing the company's platform through cloud-native and AI transformation initiatives.

As a Datacenter AI Systems and Solutions Engineer at Qualcomm, you will research, develop, and optimize end-to-end AI/ML solutions that integrate Qualcomm's AI inference accelerators with system software and ecosystem components. You will lead the design and deployment of production-ready Generative AI and LLM applications, perform model benchmarking and performance analysis, and serve as a technical lead for customer engagements on AI model optimization and inference tuning.…See more The role requires deep expertise in AI systems architecture, MLOps practices, and large-scale distributed systems, with hands-on proficiency in Python, ML frameworks, containerization, and orchestration platforms. You will drive system-level requirements, hardware/software co-design, and influence product direction through performance analysis and optimization strategies.

Design, develop, and optimize machine learning systems and models for production AI platforms, with focus on inference optimization, scalable ML infrastructure, and deployment. Responsibilities include building ML pipelines, optimizing model inference across hardware environments, integrating LLMs and models into APIs and microservices, designing data pipelines for ingestion and feature engineering, and collaborating cross-functionally on end-to-end ML solutions.…See more Requires strong software engineering fundamentals combined with deep ML expertise, proficiency in Python and at least one systems language (C++, Rust, or Go), and solid understanding of ML frameworks, transformer architectures, and model deployment systems.

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

Design, develop, and optimize real-time embedded modem software for Qualcomm's cellular platforms (5G/6G), working close to the metal with performant C/C++ on DSP and Arm cores across protocol layers, drivers, and RTOS components. Own end-to-end feature delivery from requirements through on-target validation, with strict latency, memory, and power constraints.…See more Pioneer AI-native development practices by integrating code-generation agents, LLM-based code review, and automated test synthesis into daily workflows to accelerate delivery and debugging. Debug complex multi-layer issues on target hardware, increasingly leveraging AI-assisted log and crash analysis.

Design, develop, and optimize machine learning systems for production AI platforms, including model development, inference optimization, and scalable ML infrastructure. Build training-to-deployment pipelines, optimize model serving for latency and cost, and integrate LLMs and generative AI models into microservices and APIs.…See more Develop data pipelines for ingestion, preprocessing, and feature engineering while collaborating cross-functionally with product, platform, and hardware teams to deliver end-to-end ML solutions.

This is a hands-on security engineering role focused on running Saronic's cyber threat intelligence program. The engineer will track nation-state and advanced criminal adversaries targeting the defense industrial base, operationalize indicators and TTPs into detections and hunts, produce finished intelligence products, and fuse external threat feeds with internal telemetry to prioritize real exposures.…See more The role requires 4+ years in cyber threat intelligence, threat hunting, detection engineering, or intrusion analysis with demonstrable experience tracking sophisticated or state-sponsored adversaries.

As a Senior Systems Engineer for Data Center AI at Qualcomm, you will research, develop, optimize, and validate AI/ML solutions that integrate Qualcomm's hardware accelerators with software and ecosystem to deliver high-performance inference in datacenter environments. You will design and deploy Gen AI and LLM applications, implement fine-tuning and distillation techniques, perform model benchmarking, and drive system-level architecture decisions.…See more You will collaborate across functional teams to meet system-level requirements while staying current with advances in AI/ML models and hardware. Required skills include strong Python proficiency, expertise in ML frameworks (PyTorch, TensorFlow), deep understanding of ML deployment and system performance profiling, and experience with parallel computing.

Own and deliver small to medium machine learning system components from design through production deployment, including building data pipelines, training and evaluating models, and implementing MLOps monitoring. Write high-quality Python code to translate technical requirements into maintainable solutions, working with frameworks like scikit-learn, TensorFlow, PyTorch, and HuggingFace.…See more Design and deploy ML models as microservices, APIs, batch jobs, or streaming components on AWS, with responsibility for model performance metrics, data drift detection, and retraining triggers. Collaborate across Data Engineers, Software Engineers, Data Scientists, and product stakeholders to deliver project objectives.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers.…See more Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

Build the foundational agentic AI layer for a materials-science platform, including multi-model provider abstraction, agent orchestration with stateful checkpoints, retrieval systems, prompt versioning, and comprehensive tracing and evaluation frameworks. You'll design agents that plan and reason over tool calls in production, implement human-in-the-loop safety gates, and ensure all LLM behavior remains auditable and cost-tracked across customers' secure environments.…See more The role demands deep production experience with agentic and LLM systems: async Python, structured outputs, memory and context management, multi-step workflow orchestration, and evaluation harnesses that catch regressions before deployment.

As a Data Developer, you will design, develop, and maintain scalable ETL/ELT pipelines and cloud-based data platforms that integrate enterprise systems and support AI/ML initiatives for the U.S. Navy.…See more You will perform data engineering tasks including cleansing, transformation, and optimization of SQL and Apache Spark workloads on AWS, while also developing predictive models and generative AI solutions using Python-based technologies. You will build interactive dashboards and visualizations in Tableau or Qlik, translating technical findings into actionable insights for stakeholders. An active Secret clearance, U.S. citizenship, and a bachelor's degree in a technical field (or 4+ years of relevant professional experience) are required.

The Applied AI Engineer develops, deploys, and maintains generative AI solutions for insurance products and internal workflows. The role involves implementing end-to-end AI pipelines using AWS services (SageMaker, Lambda, ECS/EKS, S3), building feature engineering workflows in Snowflake, and collaborating with cloud and MLOps teams.…See more Candidates need 3+ years of AI/ML engineering experience with 1–2 years focused on generative AI or LLMs, proficiency in Python and frameworks like PyTorch or Hugging Face Transformers, and hands-on cloud deployment experience. The position requires monitoring model performance, ensuring security and compliance, and supporting AI architecture reviews.

Design and build large-scale multimodal foundation models that integrate high-dimensional biomedical imaging with molecular and language data. You will implement cross-domain data fusion strategies, develop high-performance ML pipelines for petabyte-scale datasets, and collaborate with scientists and engineers to translate biological complexity into scalable, production-ready code.…See more The role requires deep expertise in Computer Vision architectures, distributed training frameworks, and expert Python proficiency. You will contribute through high-impact publications or open-source work and demonstrated ability to handle the noise and sparsity inherent in biological data.

Qualcomm seeks a Machine Learning R&D leader to design and deliver Agentic AI systems for hardware design automation. The role combines hands-on technical execution with team leadership, requiring deep expertise in generative AI, large language models, and ML/AI product development.…See more Responsibilities include architecting end-to-end ML solutions, coaching an interdisciplinary team of researchers and engineers, and bridging research prototypes into production design tools. The ideal candidate brings PhD-level credentials, 2+ years of industry ML/GenAI experience, and proven expertise in agentic AI frameworks, foundation models, and complex ML software pipelines.

Lead Veracyte's Quality Engineering Platform team as Manager of Software Test Automation, defining quality strategy and building scalable automation frameworks that enable product teams to own software quality. Manage a team of SDETs, Automation Engineers, and Quality Platform Engineers to develop self-service testing platforms, reusable automation libraries, and AI-assisted quality tools supporting unit, integration, API, UI, end-to-end, regression, performance, security, and compliance testing.…See more Establish modern engineering practices, quality standards, and reference architectures across the organization while fostering a culture of innovation and continuous improvement. Drive Veracyte's strategy for AI throughout the software testing lifecycle, including automated test generation, regression analysis, defect classification, and synthetic test data creation.

This intermediate-level role develops AI-enhanced decision systems for government sponsors, applying machine learning, large language models, and decision science to mission-critical problems. You will design, prototype, and evaluate AI solutions in cross-functional teams, lead R&D initiatives, and work hands-on with modern AI techniques including deep learning, reinforcement learning, generative AI, and multi-agent systems.…See more The role requires 2+ years of hands-on ML experience (or 1 year with a Master's degree) and proficiency in Python and/or C++, with the ability to communicate complex technical concepts to both technical and non-technical audiences.

Junior AI Software Developer supporting Navy cybersecurity and mission operations in San Diego. You will participate in problem discovery with mission stakeholders, contribute to technical solution design, and deliver hands-on implementation of scripts, APIs, automation, and AI/LLM-enabled workflows.…See more Work involves integrating systems via REST/HTTP APIs, writing and testing Python code, using version control, and documenting technical solutions for both technical and non-technical audiences while adhering to RMF, security controls, and responsible AI practices in classified or controlled environments.

Senior AI Software Developer who will design, implement, and integrate AI/LLM-enabled solutions and automation for Navy cybersecurity and mission workflows. You'll work in small, multidisciplinary teams translating mission requirements into technical approaches, delivering hands-on code (Python, APIs, data integration), and ensuring solutions align with RMF, security controls, and compliance boundaries.…See more The role blends advisory conversations with focused implementation of secure, deployable systems that reduce cyber risk and improve operational efficiency. Success requires 4+ years of software development or integration experience, Python proficiency, API and data store expertise, cloud or enterprise deployment knowledge, and ability to communicate across technical and non-technical stakeholders.

An AI Software Developer at Booz Allen Hamilton will design, implement, and integrate AI-enabled automation and analytics solutions for Navy cybersecurity and mission workflows. The role requires hands-on Python development, API integration, and secure system design in classified or controlled environments, with close collaboration between cybersecurity specialists, engineers, and mission stakeholders.…See more Success demands translating mission requirements into technical tasks, delivering credible implementations (not slide-only recommendations), and operating within RMF, compliance, and secure engineering practices. The ideal candidate combines software engineering rigor (version control, code review, testing) with AI/LLM experience and the ability to work in small, structured teams on multidisciplinary problem-solving.

As a Sr. Staff Software Engineer on Qualcomm's AI Software team, you will design and develop the Qualcomm AI Runtime (QAIRT) SDK for IoT platforms, enabling efficient execution of deep neural networks, LLMs, and modern AI architectures.…See more You will lead feature development, mentor junior engineers, and collaborate across cross-functional teams to deliver scalable AI software solutions. The role requires 8+ years of software development experience with strong C/C++ and Linux proficiency, hands-on technical leadership, and the ability to keep pace with rapid industry and academic advances in machine learning and software engineering.

Design and implement software integrations connecting lab automation infrastructure (liquid handlers, plate readers, robotic workstations, analytical instruments) with orchestration layers and digital workflows. Build production-grade Python applications and containerized services using Docker and Kubernetes, deploy CI/CD pipelines, and maintain LIMS integrations.…See more Explore AI-driven decision-making and autonomous orchestration capabilities, staying current with LLM tooling and agent frameworks. Provide technical leadership and mentorship to the automation engineering team while shaping the roadmap for closed-loop autonomous discovery systems.

As an AI Software Engineer at Qualcomm, you will develop and optimize machine learning software for the Qualcomm AI Stack (QAIRT and Genie SDKs), enabling efficient execution of large language models and deep neural networks on Snapdragon platforms. You will validate and optimize performance of generative AI models, debug complex issues, and collaborate across teams to deliver robust AI solutions.…See more The role requires strong software design, programming, and debugging skills, with expertise in machine learning frameworks, embedded systems optimization, and languages like Python or C++. You will work with minimal supervision, participate in design reviews, and contribute to a culture of technical excellence.

Senior Applied AI Engineer at West Health will design, build, and deploy production-quality AI-powered tools and workflows using large language models, multi-agent architectures, and orchestration platforms. The role involves building intelligent automation pipelines with tools like n8n, LangChain/LangGraph, and Microsoft Copilot Studio, integrating AI capabilities with existing data infrastructure (Snowflake, Python), and conducting data analysis to identify high-impact AI opportunities.…See more The ideal candidate combines deep practical expertise in applied AI with the ability to rapidly move from concept to fully working, well-documented applications that create measurable value for healthcare delivery and senior care initiatives.