model-evaluation jobs in San Diego

Lead the design, development, and deployment of enterprise-scale Generative AI and LLM solutions across Azure and AWS environments. Define AI architecture frameworks, standards, and governance practices while architecting RAG systems, agentic AI, multi-agent systems, and vector database solutions.…See more Partner with business leaders and engineering teams to translate business requirements into scalable, secure, and responsible AI platforms. Mentor architects and data science teams while evaluating emerging AI technologies and driving innovation initiatives.

Build production AI features and services using foundation model APIs, retrieval-augmented generation (RAG), and agentic workflows. You will implement scalable microservices in Python or Java, develop evaluation and quality frameworks for AI systems, and collaborate across teams to integrate AI capabilities into enterprise workflows.…See more The role requires hands-on applied AI experience, strong backend or platform engineering skills, and familiarity with vector databases, LLM orchestration tools, and cloud infrastructure.

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.…See more 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.

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.…See more 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.

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.

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.

Lead a specialized team of software engineers developing innovative Pixel sensor experiences at the intersection of hardware, software, and AI. You will drive the design and implementation of real-time embedded systems that process sensor signals efficiently while applying machine-learning and signal-processing algorithms in a power-optimized manner.…See more Required: 8 years software development experience, 5 years in computer vision or signal processing, 5 years leading ML design and infrastructure optimization, and 3 years technical leadership. This role demands deep expertise in embedded software, AI/ML algorithms, sensor fusion, and the ability to independently architect systems while managing a team.

The AI Architect will lead the design, development, and deployment of enterprise-scale generative AI solutions across Azure and AWS, partnering with business and engineering leaders to define AI strategy and architecture standards. The role requires deep expertise in modern LLMs (Claude, Gemini, OpenAI), multi-cloud AI platforms, and enterprise architecture, with 10+ years in software/cloud architecture and 5+ years architecting AI/ML solutions.…See more Key responsibilities include designing end-to-end GenAI solutions leveraging RAG, agentic AI, and multi-agent systems; establishing cloud-native deployment patterns; and defining governance, compliance, and responsible AI frameworks. The ideal candidate will serve as a trusted technical advisor to executives, mentor engineering teams, and drive AI adoption through reusable frameworks and reference architectures.

As Principal Software Engineer for AI & Data Platform, you will architect the data foundation for scientific and engineering R&D platforms, designing scalable data processing patterns, ML training pipelines, and intelligent workflow interfaces. You will own end-to-end responsibilities including data modeling for multi-use analytics and ML, building production training and fine-tuning pipelines, model evaluation and benchmarking, and setting engineering standards for the team.…See more The role requires 10+ years shipping production software, expert-level Python, deep experience with large-scale data systems (object storage, analytical processing, training formats), hands-on ML pipeline development, and the ability to set technical direction in early-stage environments while implementing it yourself.

Ignite Digital seeks an AI Engineer to own the end-to-end machine learning lifecycle—from data preparation and model training through production deployment and monitoring. You will integrate AI models into frontend and backend systems, optimize performance for latency and cost, and collaborate with technical leads and customers to deliver Data and AI solutions.…See more The role requires strong Python and cloud platform expertise (AWS, Azure, or GCP), software engineering fundamentals, and the ability to communicate technical opportunities and limitations across varying levels of technical experience.

Lead end-to-end product management for advisor-facing AI experiences within LPL Financial's AI Business Solutions team. Own product vision, roadmap, and delivery lifecycle from opportunity framing through commercialization and scaled adoption.…See more Define advisor chat and agentic AI capabilities, evaluate third-party AI vendors, and ensure measurable business impact aligned to enterprise OKRs. Collaborate in a four-in-a-box model with Technology, Business, and Operations & Risk to co-design product definitions, data contracts, evaluation frameworks, and governance documentation.