ai jobs in San Diego

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.

Design and develop software applications orchestrating complex automated laboratory workflows, closed-loop learning systems, and AI-integrated autonomous discovery ecosystems for biotherapeutics research. Build data pipelines, visualization tools, and machine learning models for visual inspection, predictive maintenance, and process optimization.…See more Create digital lab infrastructure including IoT integrations, digital lab twins, telemetry monitoring, and integrations across automation schedulers, LIMS, and data platforms. Requires Ph.D. in Computer Science/Software Engineering/Bioengineering with 3+ years industry experience (or M.S. with 10+ years, or B.S. with 13+ years), preferably in pharmaceutical or automation sectors.

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 the design and deployment of AI-powered marketing automation workflows, predictive analytics frameworks, and performance dashboards across Intuit's marketing organization. Build production-grade automation infrastructure on cloud platforms (GCP/AWS/Azure) that integrates AI tools into the marketing tech stack, operationalizes customer segmentation models, and scales intelligent automation globally.…See more Develop dashboards, attribution models, and automated reporting pipelines that quantify adoption, cost savings, and performance lift. Partner cross-functionally with product, engineering, data science, and marketing teams to architect, validate, and transition high-impact AI pilots into enterprise capabilities.

Lead the development of autonomy software for advanced sensor systems and uncrewed platforms, integrating hardware and algorithms into robust, real-time fielded solutions. You will architect and implement C++ applications using modern software practices (CI/CD, TDD, open architecture), lead small engineering teams through system development and test cycles, and engage directly with Air Force, Navy, and DARPA customers to shape product direction.…See more The role requires converting higher-level algorithms (MATLAB) into production-grade, multi-threaded C++ for safety-critical, real-time embedded environments, supported by live testing and modeling-and-simulation infrastructure.

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.

This Cybersecurity Manager role owns vulnerability and exposure management, leads penetration testing, threat hunting, and threat intelligence programs. The position integrates AI and machine learning into security operations to enhance threat detection and anomaly identification, manages security tools and incident response, and ensures the security of AI/ML systems across the enterprise.…See more The candidate will develop automation scripts and SOAR workflows, conduct forensic investigations, and drive continuous improvement in the security posture. Required qualifications include 5+ years of cybersecurity experience, a relevant bachelor's degree, and an industry-recognized certification (Security+, SSCP, CCNP Security, CISSP, or equivalent).

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.

The Senior AI Data Engineer will architect and build Cortica's data ecosystem, owning end-to-end projects from requirements through production deployment. Responsibilities include designing scalable data pipelines, developing data models for clinical and financial reporting, and building internal tools and dashboards.…See more The role requires 5+ years of production data pipeline experience, 2+ years with AI-first development workflows, advanced Python and SQL proficiency, 4+ years with AWS/Azure big data services, and 2+ years with orchestration frameworks.

Qualcomm seeks an embedded software engineer to design and develop core software frameworks across the Snapdragon processor stack, with focus on AI/ML acceleration, inter-processor communication, memory management, and DSP optimization. You will work on low-level system software powering machine learning inference, computer vision, multimedia, automotive, and IoT applications.…See more The role requires strong C/C++ skills, deep understanding of operating systems, RTOS, multicore architectures, and performance optimization techniques across Linux, Android, and Windows platforms.

A Principal-level GPU engineer role requiring architecture, design, implementation, and optimization of GPU cores and related software. The position involves leading teams to develop functional model simulations, graphics tests, driver and compiler software, and performance/power verification across complex GPU systems.…See more Requires 6–8+ years of software/hardware/systems engineering experience with advanced expertise in GPU architecture, and includes technical leadership and cross-functional collaboration with vendors and senior leadership.

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.

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.

Lead the design and deployment of AI agents and automation tools across Intuit's talent acquisition function. You'll partner with TA teams to identify high-impact AI opportunities, build working prototypes using LLM APIs and agent frameworks, establish governance and performance metrics for deployed agents, and translate validated solutions into production requirements with engineering teams.…See more This role requires both deep TA domain expertise and hands-on AI implementation experience—you'll move from problem discovery through prototype validation to scaled deployment while maintaining human oversight and compliance.

As a Machine Learning Application Developer, you will develop and optimize neural rendering applications and ML software for efficient AI execution on Samsung's mobile GPUs. Working with hardware and software teams, you'll optimize performance and resource utilization by developing API-level software, ML operator implementations (GEMM, convolution, activations), and conducting low-level performance analysis.…See more The role requires strong C/C++/Python skills, proficiency with Vulkan/OpenGL/OpenCL, hands-on neural rendering experience, and deep understanding of GPU architecture and performance optimization techniques.

Senior Embedded Firmware Design Engineer at Semtech responsible for defining, developing, and optimizing embedded firmware for low-power mixed-signal circuits from specification through production support. Role includes designing hardware-firmware architectures, implementing ML-based inference firmware, conducting pre- and post-silicon validation, and mentoring junior engineers.…See more Requires 8–10 years of embedded firmware experience for mixed-signal ICs, strong C/C++ and assembly proficiency, deep knowledge of MCU architectures (ARM, RISC-V, STM32), and expertise in real-time systems, signal processing, and design-for-test methodologies.

Software Engineer responsible for scoping and defining requirements, designing and implementing solutions using modern programming languages and technology stacks, and ensuring quality through secure coding practices and testing. The role involves converting customer requirements into refined visions, developing software interfaces across network protocols, integrating components into complex environments, and supporting both lab and on-site customer testing.…See more Requires 3–5+ years of relevant experience, strong understanding of SDLC, object-oriented programming, distributed systems, algorithms, and data structures. Travel up to 10% required.

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.

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.