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.
ai jobs in San Diego
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.
Google AI Lead Architect
ExpiredLead 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.
As a Staff Product Data Manager for AI Platforms & Systems Solutions at Qualcomm, you will own the product strategy, definition, and lifecycle for AI platform products and specifications spanning model enablement, agentic systems, orchestration runtimes, and open protocols. You will develop comprehensive plans of record including schedules, budgets, and resources, directing products from conception through end of life while functioning as a central resource across systems, engineering, standards, quality, marketing, and partner teams.… The role requires deep fluency in the Windows edge-AI stack, with technical depth across AI/ML models, agentic systems, orchestration engines, standards development, and hands-on experience delivering Windows-based AI products leveraging local accelerators (CPU, GPU, NPU). You will translate emerging model, agentic, and orchestration trends into differentiated product and specification roadmaps.
AI Architect
ExpiredThe 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.
The IT Business Analyst supports AMETEK's business operations through custom application development and enterprise solutions, including Oracle ERP and Microsoft Power BI. The role requires translating business requirements into IT solutions, managing custom applications, developing reports, and supporting AI initiatives by making data available to AI platforms.… Responsibilities include handling compliance reporting, end-user support, and application documentation. The position demands 5+ years of IT business analysis experience, 3+ years of ASP.NET or equivalent custom coding, and demonstrated experience in a manufacturing environment.
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.
Shield AI seeks a Staff Engineer, DevOps to own and maintain the build system for autonomous aircraft (XBAT/VBAT), with deep expertise in C++ and CMake. You will improve developer velocity by reducing build/test cycle times, integrating CI pipelines with HIL and simulation environments, and implementing monitoring and dashboards for build system performance.… The role requires 7+ years of industry experience (or 5+ with advanced degree), proficiency with containers/orchestration, scripting, CI/CD tools, and cloud operations across Azure/AWS/GCP. You'll collaborate with software engineers to resolve failures, set best practices, and leverage agentic AI solutions to identify root causes and accelerate development cycles.
As Manager, Data Operations, AI and Automation at Measurabl, you will lead end-to-end utility data quality operations for a commercial real estate ESG platform, owning quality standards, customer data health monitoring, and incident resolution. You will design and deploy AI-driven automation (agents, scripts, workflows) to resolve routine data quality issues at scale, eliminating manual work rather than staffing it.… You will manage offshore and vendor teams while serving as the technical escalation point for high-impact data quality issues, ensuring customer data meets audit and regulatory standards. Success is measured on team outcomes and automation effectiveness, not personal task routing.
AMD seeks a Principal Compiler Architect to lead the design and optimization of LLVM-based compilers for AMD GPUs, focusing on performance improvements for ML frameworks and HPC applications. The role involves working with architecture specialists on hardware bring-ups, debugging compiler issues, and developing groundbreaking compilation technologies for current and future GPU hardware.… The candidate will apply data-driven optimization strategies, stay current with hardware and software trends, and collaborate across teams to enhance compiler support for ML and HPC workloads. Required expertise includes strong C/C++ programming, understanding of GPU execution models, and ideally a track record of open-source LLVM contributions.
Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go.… Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.
This role involves independently designing, developing, and debugging real-time embedded software, RTOS environments, and microcontroller firmware for wireless chipsets supporting 3G, 4G, 5G, and AI technologies. The engineer will work on driver development, integration, testing, and validation of communication protocols and platforms, while also contributing to data collection frameworks, machine learning modeling, and embedded software algorithm improvements.… Responsibilities include on-target development, tool and process optimization, customer support, technical documentation, and active participation in design reviews. The position requires a Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related field.
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.… 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.
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.
Machine Learning Engineer
ExpiredOwn 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.
This role focuses on designing, developing, and deploying next-generation agentic automation solutions that replace and extend traditional RPA capabilities across enterprise systems. The engineer will architect AI-driven agents, chatbots, and workflow engines; lead technical delivery for a global matrixed team; and integrate platforms like Automation Anywhere with modern agentic frameworks and containerized infrastructure.… Success requires 7+ years in automation engineering or software development, strong proficiency in Python, Rust, and TypeScript, hands-on experience with agentic runtimes (n8n, LangGraph, Agno), and deep expertise in Docker, Kubernetes, enterprise security, and process optimization.
AI Architect
ExpiredThe 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.… 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.
AI Architect
ExpiredArchitect responsible for creating detailed plans and drawings using AutoCAD and Revit to outline project design, conducting site evaluations to ensure quality and safety compliance, and overseeing the construction process from conception through completion. The role requires strong organizational and creative skills, knowledge of engineering and materials science, and ability to collaborate with multiple teams on goals, schedules, and budgets.… Requires a Bachelor's degree in architecture and 3+ years of construction and architecture experience.
As a Staff Software Engineer in Data Platform Engineering, you will design, build, and operate cloud-native platform components and services, taking features from design through production. You'll lead well-scoped technical projects, collaborate with senior engineers on architecture alignment, and ensure reliability and scalability through testing and instrumentation.… You'll spend most of your time hands-on building operators, controllers, automation, and platform services that other teams depend on, while mentoring junior engineers. The role requires 8+ years of software development experience (or equivalent with advanced degrees), 5+ years of hands-on Kubernetes experience, and proficiency with at least one major hyperscaler (AWS, Azure, GCP).
Own the complete release and deployment strategy for Elemynt's secure AI infrastructure platform, building systems that ensure every release is versioned, reproducible, observable, and safe to operate across enterprise and scientific computing environments. Design and implement deployment automation, CI/CD pipelines, artifact management, and operational visibility (logs, metrics, alerts) that work reliably in customer-managed and restricted environments.… Debug incidents, identify root causes, and systematize fixes into reusable automation. Partner with product and engineering teams to embed deployment readiness into the platform from the start.
Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams.… The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.
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.