Zensar is seeking an experienced AI Architect to design, develop, and deploy enterprise-scale AI and Generative AI solutions. The role requires deep expertise in Large Language Models (Claude, Gemini, OpenAI), multi-cloud platforms (Azure, AWS), and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years designing AI/ML solutions.… Responsibilities include defining AI strategy and architecture standards, designing end-to-end GenAI systems (RAG, agentic AI, multi-agent systems), architecting secure infrastructure across Azure and AWS, establishing governance and responsible AI frameworks, and leading adoption programs. The ideal candidate will mentor teams, evaluate emerging technologies, and translate business requirements into scalable, production-grade AI systems.
llm-large-language-models jobs in San Diego
Conduct cutting-edge research in efficient generative AI, including LLMs, multi-modal foundation models, LLM reasoning, reinforcement learning, and agentic AI. Lead high-impact research initiatives and develop production-ready solutions with real-world commercial impact, with a focus on on-device deployment challenges.… Implement and evaluate solutions in both simulation and on-device environments, and publish findings in top-tier AI/ML conferences. Requires a Master's degree and 2+ years of experience (or PhD), with proven research excellence, deep expertise in generative AI and reinforcement learning, and hands-on experience with model development pipelines including training, fine-tuning, evaluation, and optimization.
As a Staff Software Engineer on Qualcomm's AI Software team, you will lead design and development of core features in the Qualcomm AI Stack (QAIRT and Genie), optimizing deep neural networks and large language models for execution on Snapdragon mobile platforms. You will drive AI runtime framework components for resource-constrained mobile systems, working closely with OEM partners and customer teams to deliver features, optimizations, and bug fixes required for product launches.… The role demands expertise in optimizing for power, memory, and performance constraints while maintaining high code quality through design reviews and mentoring junior engineers. You will debug complex system issues across software-hardware boundaries and proactively improve developer workflows, tools, and documentation.
As an Anthropic Forward Deployed Engineer, you will embed with government and public services clients to identify business needs and rapidly prototype GenAI-enabled solutions using Claude and related Anthropic technologies. You'll build production-quality AI solutions, agentic platforms, and workflows while working independently and collaborating with senior stakeholders to drive measurable business impact.… The role requires 4+ years of software/data engineering experience, 1+ years hands-on with GenAI/LLM solutions, and demonstrated expertise with Anthropic's platform technologies including Claude API, tool use, and extended thinking. You'll develop scalable AI patterns, contribute reusable assets, and mentor team members while balancing quality, safety, latency, and cost considerations.
Lead the design and delivery of enterprise AI platforms and applications on Google Cloud, leveraging Vertex AI, Gemini, and cloud-native technologies. Design, fine-tune, and govern LLM solutions; build RAG and agentic systems; and define end-to-end architectures spanning data pipelines, feature engineering, model lifecycle, APIs, and MLOps/LLMOps.… Architect cloud-native applications on GKE, Cloud Run, and managed services while implementing security, governance, and production-grade monitoring for AI/ML systems at scale.
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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.
S. Navy.… a 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. 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.… 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.… 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.… 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.… 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.… 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.… 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.… 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.