ai jobs in San Diego

Senior AI Engineer role focused on designing and leading scalable, high-performance data architecture solutions that support AI/GenAI use cases. The role involves building and optimizing data pipelines, defining database schemas (Graph, SQL, NoSQL), and leading infrastructure for AI model deployment across cloud and on-premises environments.…See more Requires 4+ years in data engineering/MLOps with hands-on AWS/Azure/GCP experience, 2+ years managing technical teams, and expertise in DevOps, CI/CD, containerization (Kubernetes, Docker), and ML deployment frameworks. The position includes mentoring junior engineers and driving technology modernization initiatives.

Senior forward-deployed engineer at Deloitte GPS responsible for developing scalable AI engineering patterns and production-quality GenAI/LLM solutions for government clients. Must have 7+ years software/data engineering experience, 1+ years hands-on with Palantir (Foundry, AIP, or Maven), and 1+ years building and deploying LLM-powered solutions in production.…See more Role emphasizes architecture balancing quality, safety, latency, cost, and model risk; delivering well-tested, documented code with strong CI/CD practices; and translating business problems into AI solutions while leading technical workstreams.

This is a hands-on Solution Architect role for an AI-enabled Managed Services team, requiring deep technical expertise in designing end-to-end application architectures spanning UI, APIs, services, data, and AI components. The role combines hands-on coding and prototyping with architecture ownership, emphasizing active participation in codebases, AI tool evaluation, and guiding engineering teams through complex technical decisions.…See more Key responsibilities include designing reference architectures for AI patterns (RAG, vector search, prompt orchestration), defining non-functional requirements (performance, reliability, security), architecting CI/CD pipelines, and ensuring production readiness. The ideal candidate has 8+ years of software engineering experience, strong cloud-native and modern application architecture knowledge, practical AI feature development, and comfort working directly in code and infrastructure.

AfterQuery seeks software engineers with 2+ years of real-world experience to complete AI model training and evaluation projects on a remote, asynchronous basis. Responsibilities include code review, model output evaluation, and original task creation across a range of AI training initiatives.…See more Work is fully independent and project-based, with hourly rates ranging from $50–$100 depending on project qualification.

As a Senior Consultant on the Cloud Cyber Risk team, you will deliver Azure cloud security engagements spanning governance, identity, application security, infrastructure, AI security, monitoring, and data protection. You will perform security assessments, solution design, implementations, and health checks across Azure, Microsoft Entra ID, and Microsoft 365 environments, working directly with clients to identify risks and recommend configurations.…See more You will develop technical deliverables including assessment reports, architecture diagrams, and remediation documentation. The role requires 4+ years of technical consulting or cloud security implementation experience, hands-on design and implementation in Azure or hybrid cloud environments, expertise with Azure Policy, Terraform, or JSON-based infrastructure configuration, and 3+ years with cloud security tools (CNAPP, CSPM, CWPP).

This is a senior cloud security consulting role at Deloitte focused on designing, implementing, and managing Azure cloud security solutions across governance, identity, application security, AI security, and infrastructure. The candidate will lead client engagements and cross-functional teams, translating business requirements into enterprise cloud security architectures and strategies, with hands-on experience designing controls for Azure AI services, CNAPP/CSPM/CWPP platforms, and infrastructure-as-code tools like Terraform.…See more Success requires 6+ years of technical consulting and solution architecture in Azure, 4+ years designing cloud security solutions and enterprise architectures, and deep expertise in Azure Policy, Terraform, JSON-based infrastructure, and Microsoft AI security frameworks.

Lead ServiceNow AI implementation projects as an architect-manager, designing and deploying AI solutions (NOW Assist, Agentic, AI Control Tower) with hands-on expertise in prompt engineering, LLM orchestration, and RAG techniques. Configure Moveworks for automated ticket resolution and integrate multiple AI models within ServiceNow workflows.…See more Conduct client design sessions, manage project delivery across waterfall and agile models, and lead technical teams while supporting pre-sales efforts.

As a Data Engineer at Booz Allen Hamilton, you will design, develop, and deploy data pipelines and platforms that organize disparate data sources to support mission-critical analytics workloads. You'll work with ETL operations, relational and non-relational databases, and collaborate with analysts, developers, and data scientists in an agile environment.…See more Required skills include Python, SQL, Git, Linux/Windows automation, and experience with pipeline development or systems administration. The role emphasizes building scalable, maintainable data infrastructure that transforms raw data into actionable insights.

Lead validation of clock, power, reset, and power-management architectures for next-generation AI accelerator SoCs, owning pre-silicon and post-silicon validation of clocking infrastructure, PMIC integration, DVFS, and low-power features across multi-die systems. Develop bare-metal validation frameworks, test plans, and automation using C, Python, and Perl; debug complex power, performance, and stability issues in collaboration with architecture, design, verification, and firmware teams.…See more Define validation methodologies and stress workloads for AI training and inference scenarios, and drive power subsystem bring-up readiness across program milestones. Requires 5+ years of SoC validation experience, proficiency in C and Python, hands-on lab instrumentation skills, and prior exposure to clock and power validation.

Lead end-to-end DDR validation for next-generation LPDDR5X/LPDDR6 memory subsystems on AI Accelerator and mobile platforms, spanning pre-silicon through post-silicon phases. Drive memory bring-up, performance validation, system stress testing, and debug across emulation, FPGA, and silicon platforms.…See more Develop validation strategies, automation, and regression infrastructure while partnering with architecture, design, firmware, and vendor teams to resolve DDR controller, PHY, and system-level issues. Require 5+ years of DDR/memory subsystem validation experience, deep knowledge of LPDDR architectures, DDR controllers/PHYs, memory training algorithms, and strong post-silicon debug skills with C/C++ proficiency.

This role blends data science expertise with hands-on automation engineering to design and deploy intelligent process automation solutions across business units. You will build, train, and validate both classical ML and LLM-based models — including fine-tuning and RAG — and architect end-to-end systems connecting CRM, APIs, and AI services on AWS infrastructure.…See more Responsibilities span solution design, CI/CD implementation with Jenkins, Python development, agentic AI capabilities, and business translation, with emphasis on measurable business outcomes and compliance.

Design, build, and operate production-quality agentic AI systems and developer tooling at scale. Lead multi-agent orchestration, Model Context Protocol (MCP) integration, prompt engineering for structured output, and CI/CD automation for code review and testing.…See more Partner with engineering teams on discovery, rapidly prototype and validate capabilities, then own the full lifecycle from implementation through production monitoring. Mentor engineers on agentic design patterns and communicate technical tradeoffs to stakeholders.

As an AI Quality Assurance Engineer on the BIOVIA R&D Quality team, you will design and execute test automation for AI virtual assistants and cloud/on-premise bioscience software. You'll use ML/LLM testing expertise and hands-on AI agent experience to reduce validation turnaround time and improve software release quality.…See more The role requires proficiency in Python, TypeScript, or JavaScript; familiarity with software development processes and testing methodologies; and direct exposure to ML/LLM systems as both a user and tester.

Lead system-level validation strategy and test content development for Qualcomm's next-generation AI accelerator platform, spanning emulation and silicon phases. Own bare-metal software development, hardware–software integration, and multi-processor system testing with focus on concurrency, clock/power management, and low-level hardware interfaces.…See more Debug complex SoCs with limited visibility, support pre-silicon (simulation, emulation, FPGA) and post-silicon bring-up, and lead geographically distributed engineering teams to deliver high-quality validation solutions at scale.

Build production AI features and workflows powered by large language models, including retrieval-augmented generation (RAG), agentic orchestration, and tool/function calling integrations. You will design and implement scalable microservices in Python or Java that connect foundation model APIs to business data and internal systems, with responsibility for AI quality, evaluation, observability, and safe deployment on AWS.…See more Collaborate with cross-functional teams to prototype solutions, measure outcomes, and move proven capabilities into production while maintaining reliability, security, and auditability.

As an AI Quality Assurance Engineer, you will design and execute test automation for AI virtual assistants and cloud/on-premise bioscience software within the BIOVIA product suite. You will leverage ML/LLM systems knowledge, AI-assisted coding tools, and hands-on automation experience to reduce validation turnaround time and improve software release quality.…See more The role requires proficiency in Python, TypeScript, or JavaScript, familiarity with distributed test automation frameworks, and the ability to collaborate closely with development teams in a fast-paced, multi-threaded environment.

Design and optimize video analysis, quality assessment, and encoding algorithms for hardware-accelerated video codec solutions (FPGA/ASIC). Develop C-models and firmware implementing deep learning techniques (CNNs, Transformers, MLLMs) for video processing, ROI detection, and frame-level rate control.…See more Collaborate with infrastructure teams to integrate algorithms into production VOD and live-streaming pipelines, validate performance through A/B testing, and participate in objective video quality evaluation using metrics like VMAF, PSNR, and SSIM.

The Software Test Engineer will design, build, test, and deliver integrated software solutions for complex, mission-critical DoD systems. Responsibilities include testing software across mission systems, gathering requirements, developing test plans, and building/maintaining CI/CD pipelines for containerized deployments.…See more The role requires 3+ years of experience with version control, programming languages (C++, Python, Java, JavaScript), containers (Docker/OCI), SQL/relational databases, and Linux command-line usage, plus ability to work with modern frontend frameworks and DevSecOps practices.

Lead the scientific vision and execution of a generative AI platform for protein foundation models, starting with antibody and VHH design. You will build and manage a team of AI researchers and ML infrastructure engineers, define pretraining and post-training strategies across self-supervised learning, reinforcement learning, and transfer learning, and design confidence heads with out-of-distribution detection.…See more This is a founding role requiring deep expertise in structure-based generative modeling, multi-node GPU training, and the ability to shape cutting-edge computational approaches for therapeutic molecule discovery.

As an AI/ML advisor for biotherapeutics at Eli Lilly, you will lead training and fine-tuning experiments on proprietary infrastructure (LillyPod), curate and process biological data (sequences, structures, assays), and build evaluations that connect model outputs to experimental results. You will diagnose model failures, collaborate cross-functionally with protein scientists and wet-lab teams, and communicate findings to both computational and experimental audiences.…See more The role requires a Ph.D. in a quantitative field (or M.S. with 3+ years experience) and strong hands-on expertise in Python, PyTorch, and deep learning on GPUs, with preference for experience in geometric deep learning, protein language models, diffusion/flow-matching, and published ML applications to molecular data.

Designs and develops full-stack software for web applications and engineering tools, working across the data, integration, API, and UI layers. Writes reliable, testable, and maintainable code under supervision; completes technical tasks for system integrations, APIs, and software lifecycle pipelines.…See more Manages the development process from development through production release in collaboration with IT teams. Requires 2+ years of programming experience (Java, Python, etc.) and 1+ year with data structures, algorithms, and data stores.

Staff HRIS Analyst responsible for configuring and supporting Workday Time Tracking, Absence, Benefits, and payroll integrations in a complex global organization. The role requires hands-on Workday configuration expertise, defining data mappings and reconciliation for payroll and benefits interfaces, leading end-to-end solution design, and planning releases with comprehensive testing strategies.…See more Responsibilities include diagnosing complex system and interface issues, leading HR technology initiatives from requirements through stabilization, and coaching team members on functional design and controls. The candidate must have 8+ years of related experience (or equivalent with advanced degree) with substantial Workday hands-on expertise and strong analytical and communication skills.

Lead enterprise CRM transformation programs for Life Sciences organizations, owning complex Salesforce and Veeva implementations from strategy through delivery. Direct large, geographically distributed teams across solutioning, commercial operations, field force effectiveness, and omnichannel engagement.…See more Drive sales cycles end to end—from pipeline building through RFP response, pricing, and negotiation—while identifying and scaling AI/ML use cases for customer insights, targeting, and commercial decision-making. Accountable for scope, quality, financial performance, and business outcomes on multi-year transformations.

As a Software Test Engineer Intern, you will integrate and test software solutions across Innovative Defense Technologies' Integrated Mission Systems, working with developers, systems engineers, and subject matter experts to ensure high-quality, fully performing software. You will gather user requirements, define system functionality, and develop comprehensive test plans for applications written in Java, C++, Python, and JavaScript.…See more The role requires a strong foundation in application development with Java or C++ in Linux or Windows environments, along with the ability to provide actionable feedback to improve software quality and system integration.

Senior AI/ML Engineer responsible for shipping end-to-end production ML systems that enable autonomous medical coding in a SaaS platform. Will design robust ML architectures with low-latency inference, build reliable data and model pipelines using modern MLOps practices (CI/CD, model registries, experiment tracking), establish evaluation strategies with statistical rigor, and implement model observability and governance including drift detection and bias assessments.…See more Requires 5+ years of industry experience building and operating ML systems in production, 3+ years with C# or Python, 3+ years on Azure, and 1+ years of LLMOps expertise including prompt engineering and RAG.