llm-large-language-models jobs in San Diego

Principal Systems Architect responsible for defining and maintaining the technical architecture of a complex enterprise automation ecosystem spanning RPA, Machine Learning, and GenAI. Will architect data pipelines integrating diverse enterprise systems (SAP, ERP, QMS, PowerBI, Windchill, Atlassian), provide technical leadership on workflow automation and DevSecOps infrastructure, and ensure end-to-end cybersecurity compliance with DoD standards and CMMC.…See more Role requires 14+ years of progressive IT systems architecture experience, demonstrating systems engineering expertise in complex data integration, AI/ML automation, and secure deployment across engineering, manufacturing, quality, and finance domains.

Senior AI Subject Matter Expert responsible for developing intelligent data processing and NLP pipelines, AI-enabled dashboards, and proofs-of-concept for AI use cases. The role requires 7+ years of professional experience with advanced expertise in LLM APIs, RAG architectures, agent-based development, generative AI coding tools, and secure AI deployment patterns.…See more Responsibilities include prototyping emerging AI developer tooling, mentoring engineering teams on generative AI workflows, and identifying software lifecycle areas that can be accelerated through AI and automation. The candidate must critically evaluate AI-generated code for correctness and security, understand AI-specific security risks across the full SDLC, and scope requirements for engineering solutions that meet business challenges with measurable outcomes.

Design, implement, and optimize advanced algorithms for radar, optical, and infrared sensor systems, working with scientists and engineers to build high-performance backend systems for scientific computing in distributed environments. Translate existing code for GPU/CUDA acceleration, integrate and refactor scientific codebases, and work in Linux/Unix environments.…See more Requires 6+ years of C/C++ backend development (or 4+ with a Master's), expertise in high-performance computing, parallel/distributed processing (MPI), GPU/CUDA programming, and foundational knowledge of AI/ML and LLM concepts.

Senior Associate AI Engineer will develop GenAI/LLM applications and integrations using foundational models, build and test AI models and conversational agents, and configure AI solutions into enterprise applications on cloud platforms. The role requires assisting with data preparation for model training, documenting technical workflows, and staying current on emerging AI tools.…See more Requires minimum three years of professional or academic experience in AI/ML, data science, or software engineering, proficiency in Python or similar languages, and hands-on experience with a major cloud AI platform (Azure AI, AWS Bedrock, or Google Cloud Vertex AI).

Software Engineer at Eli Lilly developing oncology applications that integrate laboratory systems, data pipelines, and enterprise platforms. The role requires 5+ years of software engineering experience and involves building AI-enabled capabilities, designing scalable APIs and web applications, deploying to AWS cloud infrastructure, and owning application reliability and lifecycle.…See more Key responsibilities include implementing data quality standards, contributing to CI/CD and containerization practices, mentoring junior engineers, and working directly with scientific and operational stakeholders.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

Design and develop embedded and cloud edge software applications focused on AI/GenAI, multimedia, and computer vision SDKs and frameworks for IoT products including drones, cameras, and AI boxes. Collaborate with systems, hardware, and architecture teams to build high-performance, real-time embedded software solutions.…See more Lead GenAI LLM/VLM inference workflows, multi-stream AI pipelines, and multimedia frameworks across Android, Linux, and embedded systems. Requires 2+ years of software engineering experience with C/C++, Python, or Java, plus preferred expertise in PyTorch, TensorFlow, ONNX Runtime, LangChain, LlamaIndex, Android architecture, Linux system programming, and graphics/GPU pipelines.

Build and integrate agentic AI systems with physical laboratory automation platforms (Hamilton, Tecan, Opentrons) and LIMS infrastructure to autonomously design, run, and refine chemistry and biology experiments. Design multi-agent orchestration architectures with state management, error recovery, and tool integration; prototype agent planning strategies and memory systems; deploy containerized services on Kubernetes with GitOps and CI/CD.…See more Work hands-on with chemists, biologists, and automation engineers to transition prototypes into production lab operations that measurably accelerate the Design-Make-Test-Analyze cycle.

Own and evolve the software translation layer between high-level workflow logic and low-level laboratory instrument control, integrating liquid handlers, plate readers, robotic workstations, and analytical instruments. Deploy and maintain containerized services using Docker, Kubernetes, GitOps, and CI/CD practices, building scalable Python applications and data pipelines that connect experimental readouts with LIMS and downstream analysis tools.…See more Collaborate with the team to prototype AI-driven decision-making and autonomous orchestration in lab workflows, evaluating LLM tooling and agent frameworks for practical applicability. Serve as a technical authority and mentor, influencing the broader technical roadmap for autonomous discovery systems and helping grow the automation engineering team's capability.

Qualcomm AI Research seeks a Senior AI Research Quantization Engineer to develop algorithms for efficient generative AI, LLMs, and multimodal models optimized for on-device deployment. The role focuses on advanced quantization techniques, model compression, inference optimization (batching, KV caching, speculative decoding), and system prototyping using Python and PyTorch.…See more You will collaborate across hardware, software, and systems teams to enable state-of-the-art models to run on power- and memory-constrained devices including smartphones, autonomous vehicles, robotics, and IoT platforms. A Bachelor's degree plus 2+ years of related engineering experience (or Master's with 1+ year, or PhD) is required.

Lead a Palantir Forward Deployed Engineering team for the Government & Public Services practice, guiding architecture of data pipelines powering GenAI use cases. You will contribute production-quality code, enforce strong data management and CI/CD practices, and translate business problems into AI solutions while working with federal/state/local government clients.…See more The role requires 10+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment, and 1+ years working with Palantir (Foundry, AIP, or Maven), with deep familiarity in AWS, Azure, and/or Google Cloud environments.

Staff Engineer role driving Generative AI transformation across embedded software and engineering infrastructure at Qualcomm. Responsible for executing GenAI workstreams—converting engineering use cases into production-ready AI-enabled workflows for code generation, review, debugging, test automation, and documentation.…See more Will build reusable agents, prompts, MCP integrations, and evaluation flows; partner with embedded, platform, and software teams to onboard and increase adoption of secure, measurable GenAI solutions. Requires 4+ years software engineering experience, 3+ years hands-on GenAI/LLM application development, and strong proficiency in Python, C, C++, or Go with embedded systems familiarity.

A software security engineer will perform vulnerability research against software stacks, design and implement security tools and embedded software solutions, conduct code reviews and regression testing, and write technical documentation on vulnerabilities and mitigations. The role requires 2+ years of software engineering experience with languages like C, C++, Java, or Python, plus strong knowledge of Linux fundamentals, x86/ARM architectures, and reverse-engineering tools.…See more Candidates should have experience with debugging tools (gdb, strace, objdump), IDA Pro or Ghidra, Android platform tools, and familiarity with LLMs for augmenting vulnerability discovery.

Lead a forward-deployed engineering pod (2–5 engineers) architecting and delivering LLM-enabled applications, copilots, and agentic workflows using enterprise AI platforms, particularly Microsoft Azure AI Foundry. Own end-to-end GenAI solution design—from RAG pipeline governance and prompt engineering to production deployment and quality evaluation—while mentoring junior engineers, enforcing delivery standards, and translating business problems into scalable AI systems.…See more Require 7+ years of software/data engineering experience, 1+ years of hands-on GenAI/LLM deployment in production, and proven ability to lead technical workstreams in ambiguous, fast-paced client environments.

A forward-deployed engineer role at Deloitte's Government & Public Services practice focused on designing, building, and deploying GenAI/LLM-powered solutions on Databricks for federal and public-sector clients. The role requires 4+ years of software/data engineering experience, 2+ years hands-on with GenAI/LLM solutions in production, and 2+ years with Databricks platform technologies.…See more Responsibilities include delivering production-quality code with strong CI/CD and documentation practices, designing extensible functionality, leading project workstreams, and translating business problems into AI solutions while traveling approximately 50%.

Lead Qualcomm's GenAI transformation for embedded and software engineering, building reusable AI agents, agentic workflows, and developer productivity tools that scale across teams. Partner with platform and engineering teams to establish secure AI practices, governance models, and metrics while serving as a technical thought leader who shapes the organization's transition to AI-native engineering workflows.…See more Requires Principal-level technical leadership with deep expertise in generative AI, LLM-based systems, and hands-on experience deploying GenAI solutions in complex engineering environments. Collaborate on code generation, code review, test automation, and release readiness use cases while driving measurable productivity and quality improvements.

Develop software for the Qualcomm AI Stack SDKs (QAIRT and Genie) to enable execution of generative AI models and large language models on Snapdragon platforms. You will validate, optimize, and debug machine learning inference solutions, collaborating with cross-functional teams on feature development, performance analysis, and system reliability.…See more The role requires expertise in machine learning frameworks, embedded systems optimization, programming languages like Python or C++, and low-level OS/hardware interactions.

Design and implement security strategies for Abbott's cloud-based applications and medical devices, including hardening, incident response, penetration testing, and disaster recovery. Apply expertise in user authentication, certificate management, digital signatures, and cloud security architecture while ensuring compliance with ISO, FDA, and regulatory standards.…See more Leverage AI-assisted development tools and cybersecurity platforms to automate vulnerability analysis, evidence collection, and remediation tracking. Conduct hands-on web, mobile, and cloud infrastructure security testing using DAST, SAST, SCA, and vulnerability scanning tools, with demonstrated experience in product security and medical device environments preferred.

Senior Forward Deployed Engineer responsible for building and deploying production-grade AI solutions using frontier GenAI platforms (Claude, Gemini, GPT-4o) in client environments. Will lead end-to-end solution delivery, including architecture decisions, demo/POC development, and client enablement while mentoring junior engineers.…See more Requires 5+ years software/data engineering experience, 1+ years hands-on GenAI/LLM development, and demonstrated ability to translate business problems into scalable AI workflows with strong engineering practices (CI/CD, testing, documentation).

Lead development of scalable SaaS features for clinical trial platforms, owning delivery from ideation through release. Architect high-complexity microservices and real-time data systems using TypeScript, Python, React, and Node.js, while mentoring engineers and establishing engineering best practices.…See more Design relational schemas and integrate with cloud platforms (Azure, AWS, GCP); AI/LLM integration is a plus. Requires 7+ years building distributed, multi-tenant software products.

Design and develop security strategies for Abbott's cloud-based medical devices and applications, including hardening, incident response, penetration testing, and disaster recovery. Apply expertise in user authentication, certificate management, digital signatures, and cloud security architecture while ensuring compliance with ISO, FDA, and regulatory standards.…See more Conduct web, mobile, and cloud infrastructure security testing using DAST, SAST, SCA, and vulnerability scanning tools. Leverage AI-assisted development and cybersecurity tools—including building agentic AI applications—to automate security deliverables, with responsibility for evaluating AI tools for safe, policy-compliant use and mitigating AI/LLM-specific risks.

As Full Stack Engineer at Nucleus Biologics, you will develop and maintain software tools for scientists and manufacturing teams. Responsibilities include managing AWS infrastructure (EC2, RDS), maintaining Docker containers and Nginx, handling PostgreSQL schema and migrations, developing Python backends with FastAPI/Django/Flask, building React/TypeScript frontends, and resolving customer and internal issues.…See more You need strong production experience across the full stack: Python with modern web frameworks, React with current data-fetching patterns, PostgreSQL administration, and hands-on DevOps with Docker, Linux, and AWS.

Build and optimize scalable LLM inference platforms at Qualcomm's Cloud AI team, implementing advanced serving techniques like KV-cache management, speculative algorithms, and model optimization. Contribute to production serving frameworks (vLLM, SGLang, Triton, TGI) and work with customers on deployment solutions.…See more Collaborate with compiler, firmware, and platform teams to drive efficient serving through autoscaling, load balancing, and routing. Requires deep understanding of transformer architectures, strong PyTorch and Python skills, computer architecture knowledge, and hands-on experience profiling and optimizing deep learning workloads.

Lead product strategy and roadmap for Intuit's next-generation Agentic AI Platform, designing core execution frameworks, agent libraries, and SDKs that enable complex reasoning and autonomous task execution across TurboTax, QuickBooks, Mailchimp, and Credit Karma. Define extensible platform architecture, drive multi-step planning and orchestration capabilities, and ensure agent observability and trust at scale.…See more Partner closely with engineering and architects to standardize agent development, deployment, and management while mentoring other product managers on technical fluency and platform thinking.

Senior Machine Learning Engineer responsible for architecting, designing, developing, and deploying on-device AI prototype software for edge computing applications. The role requires expert-level proficiency in C++ and Python, deep knowledge of ML frameworks like PyTorch, and hands-on experience with low-level system debugging, performance tuning, and native inference driver development.…See more You will work in a multi-disciplinary research team advancing generative AI technology for the edge, including model fine-tuning, hardware acceleration, model quantization, and edge inference. A strong theoretical background in deep learning combined with embedded software development experience and modern software engineering best practices is essential.