ai jobs in San Diego

Design and architect RISC-V System-on-Chip (SoC) platforms, leveraging deep expertise in heterogeneous compute, interconnect, memory systems, security, and power management. Develop and improve analysis tools including functional/performance simulators and profilers using C++ and Python.…See more Apply systems engineering rigor to define SoC-level architectures across boot, debug, timebase management, and real-time control components. Candidates should have 4+ years of systems engineering or SoC/IP architecture experience and demonstrate proficiency in behavioral/performance modeling and analytical techniques.

Design, develop, and optimize Windows camera drivers and imaging solutions for Qualcomm Snapdragon platforms, working across kernel-mode and user-mode drivers, image signal processing, and AI-enhanced camera features. Lead camera sensor bring-up, hardware integration, and debug complex issues across the camera stack.…See more Collaborate with OEMs, hardware teams, silicon engineers, and Microsoft to deliver high-quality camera experiences. Mentor junior engineers and influence camera architecture decisions across product generations.

Senior technical leader responsible for integrating AI/ML systems into secure, scalable DoD-compliant environments. Will architect AI system deployments, establish DevSecOps practices, ensure compliance with RMF/NIST 800-53/DISA STIG standards, and provide technical guidance across engineering teams.…See more Requires deep expertise in AI/ML production systems, containerization, CI/CD, and cybersecurity controls, with hands-on experience in Python, Kubernetes, and modern infrastructure tooling.

Lead a team of data scientists at Insulet's Analytics Center of Excellence, managing the execution of global analytics and AI initiatives while maintaining hands-on expertise in data science work. You will mentor scientists, guide development of cloud-based analytics pipelines and automated machine learning solutions, and coordinate with cross-functional stakeholders across R&D, clinical, quality, and manufacturing to identify and deliver high-value data science opportunities.…See more The role requires a Master's degree with 5+ years in data science (or PhD with 3+), 2+ years in machine learning/AI, direct team management experience, and proficiency in Python/R, SQL, cloud platforms (Azure/AWS/GCP), and big data technologies like Spark/Databricks. You'll perform statistical analysis, predictive modeling, and communicate insights to executives while owning the data products portfolio and managing annual budgets.

Senior Data Engineer at Sony to design, build, and maintain scalable data pipelines, dashboards, and reporting solutions supporting PlayStation's payments, subscription, and fraud-prevention systems. Will develop AI-ready data products for analytics, automation, and machine-learning workflows in close partnership with data scientists, analysts, and global payments stakeholders.…See more Requires 7+ years in data engineering or related software/systems work, strong SQL and data modeling, proficiency in Python/Java/scripting languages, and experience operationalizing data for ML and governance. Will mentor team members, communicate technical architectures to executives, and drive platform reliability and security.

Senior Program Manager overseeing datacenter software initiatives at Qualcomm, managing cross-functional teams across multiple global design centers. Responsible for establishing plan of record, driving execution schedules, coordinating resources, and managing risks across semiconductor/AI product development.…See more Will interface with senior leadership, represent the program to stakeholders, and coordinate with engineering, product, and external teams to ensure on-time delivery and milestone achievement. Requires 7+ years of program management experience in semiconductors or telecommunications, with 3+ years on x86/ARM/RISC-V platforms and 2+ years on AI products.

Qualcomm seeks a Staff Product Data Manager for AI Platforms & Systems Solutions to define product strategy and drive cross-functional decision-making for edge AI/ML platforms, inference runtimes, and agentic frameworks. The role requires deep technical expertise in Windows-ecosystem AI platforms, LLM/VLM models (1B–150B range), edge AI APIs/SDKs, and AI middleware frameworks, combined with the ability to work independently, influence senior leadership, and manage complex multi-year initiatives across matrixed organizations.…See more Responsibilities include assessing feasibility, translating innovation into shippable solutions, negotiating partnerships, and authoring technical specifications—all with minimal supervision and significant organizational impact. The ideal candidate brings 10+ years in product management or technical roles, experience shipping AI platforms, familiarity with standards bodies, and strong communication skills to convey complex information to diverse audiences.

Senior engineer responsible for designing, building, and optimizing large-scale AI platforms for wireless, 5G, and connected devices. You will architect end-to-end AI/ML pipelines, integrate models into chipsets and cloud/edge environments, and deliver scalable inference services, tools, and SDKs.…See more Key responsibilities include model deployment, performance tuning on heterogeneous hardware, MLOps automation, and monitoring across silicon, software, and product teams.

Design and deploy generative AI solutions across firmware, embedded OS, and toolchains to automate workflows and optimize code. Partner with software, silicon, and DevOps teams to integrate AI copilots, code analysis, and test generation into existing development pipelines.…See more Evaluate AI models, develop scalable inference services, and measure their impact on developer productivity. Drive best practices for secure and compliant AI adoption in a fast-paced environment.

This role involves conducting comprehensive security assessments of AI systems and deployments, evaluating them against NIST frameworks (AI RMF, CSF, 800-53, 800-171) and other security standards. The consultant will identify AI-specific risks such as prompt injection, model misuse, data leakage, and supply-chain vulnerabilities across cloud platforms (AWS, Azure, hybrid).…See more Responsibilities include developing AI governance frameworks, policies, and controls; assessing AI development environments, model pipelines, APIs, and orchestration layers; and delivering executive-level recommendations and remediation roadmaps. Requires 7+ years of cybersecurity/consulting experience and 3+ years supporting AI/machine learning security initiatives, with strong expertise in AI threat modeling, secure AI deployment, and governance frameworks.

ServiceNow seeks a Staff Software Engineer (IC4) for their Data Platform Engineering organization to design, build, and operate cloud-native platform components and services on Kubernetes at scale. You will own well-scoped projects end-to-end, from design through production, collaborating with senior engineers and mentoring junior team members.…See more The role requires 8+ years of software development experience, 5+ years hands-on with Kubernetes, expertise in at least one major hyperscaler (AWS, Azure, GCP), and strong Go programming skills. You will focus on building operators, controllers, automation, and platform services that other teams depend on, with emphasis on reliability, scalability, operability, and infrastructure-as-code practices.

Senior Staff Software Engineer leading design and delivery of multi-tenant, distributed data platform services on Kubernetes at scale. You will mentor mid-level and junior engineers, architect highly available stateful workloads (databases, message queues, caches), and integrate AI into infrastructure and operational workflows.…See more The role requires 8+ years building production distributed systems, deep expertise in Kubernetes and at least one hyperscaler (AWS, Azure, GCP), and hands-on experience operating services like Postgres, Kafka, or Redis at scale with explicit HA, failover, and durability targets.

AI Research Scientist role focused on developing and optimizing large language models for on-device deployment on smartphones, IoT, and automotive systems. Responsibilities include researching and prototyping model compression, quantization, pruning, distillation, and inference optimization techniques.…See more The role involves collaboration with silicon, software, and product teams to design experiments, benchmark models, and translate research into production-ready solutions for 5G and edge AI applications.

Design and optimize machine learning models for deployment on edge devices including smartphones, IoT, and automotive platforms. Build end-to-end experimentation pipelines, benchmark models on real hardware, and work with cross-functional teams to move innovations into production.…See more The role emphasizes model optimization for constrained hardware environments, hardware benchmarking, and research contributions through publications and patents.

Design, train, and optimize machine learning models for 5G, wireless, and multimedia telecommunications products. Explore novel deep learning and signal processing techniques, conduct large-scale experiments, and translate research into production-ready solutions.…See more Requires strong background in machine learning, deep learning, and signal processing, with experience developing models for edge devices and chipsets.

Staff Engineer responsible for designing and implementing scalable test automation frameworks and infrastructure for machine learning systems across multiple engineering teams. The role requires expertise in validating ML pipelines across data, training, evaluation, deployment, and monitoring; testing GPU-accelerated workloads in Kubernetes; qualifying integrated hardware and software systems; and developing comprehensive integration and regression strategies.…See more Deep experience with Python automation, distributed systems testing, performance profiling, and observability is essential, along with strong system-design skills for complex, multi-tenant environments.

Lead enterprise AI platform strategy and execution at a biotech company, driving end-to-end program delivery across engineering, data, cybersecurity, and product teams. Own platform health, KPIs, and telemetry; establish governance, safety guardrails, and regulatory compliance for AI-enabled solutions in a regulated environment.…See more Define multi-year AI roadmaps, coordinate cross-functional dependencies, and orchestrate Agile delivery while partnering with legal, compliance, and tech enablement to ensure scalability, security, and enterprise adoption.

Lead product strategy and roadmap for AI-centric data center platforms and rack-level systems, including compute nodes, interconnect fabrics, power delivery, and cooling. Define system-level requirements by collaborating with silicon architects, systems engineers, and software teams while engaging directly with hyperscale and enterprise customers to gather feedback and drive early deployments.…See more Track product performance post-launch across system metrics like power efficiency and thermal headroom, and mentor a high-performing product management team.

As a Senior AI Engineer at Teradata, you will design and build agent-based AI solutions that enhance developer productivity, working on AI agents and platforms across the Software Development Lifecycle. You'll develop scalable, reliable systems with strong proficiency in backend technologies (Java, Go, Python), design RESTful APIs, work with SQL/NoSQL databases, and apply AI/ML technologies including agentic AI and LLMs.…See more The role requires 5+ years of experience in backend services, distributed systems, or data platform development, with hands-on expertise in Kubernetes, containerization, and cloud platforms. You will collaborate with cross-functional teams, mentor engineers, and stay current with emerging AI/ML and cloud-native technologies.

As a Staff Machine Learning Engineer focused on model optimization, you will create and implement ML techniques, frameworks, and tools enabling efficient discovery and deployment of state-of-the-art ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized inference/training software and compiler tools, and collaborate with cross-functional teams on joint hardware-software design.…See more The role requires 4+ years of hardware/software/systems engineering experience (or equivalent with advanced degree), deep expertise in ML frameworks (TensorFlow, PyTorch, Keras, Caffe), embedded systems optimization, and programming languages like Python or C++. You will work independently with minimal supervision, provide technical guidance to team members, and influence key organizational decisions through consultation with senior leadership.

Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training, validation, and performance optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) for radar data analysis and optimize models for real-time embedded deployment under latency, memory, and power constraints.…See more Bridge research and production by translating state-of-the-art ML techniques into scalable algorithms for radar-based detection, classification, and tracking, with strong requirements in signal processing, statistical analysis, and Python/PyTorch/TensorFlow proficiency.

Lead and manage a team of IT engineers while driving the design, development, and implementation of IT infrastructure, systems, and applications. Ensure IT solutions align with company objectives, maintain engineering standards and policies, and optimize system performance and security.…See more Collaborate cross-functionally to understand IT requirements and evaluate emerging technologies for adoption. Monitor vendor relationships, manage contracts, and lead initiatives to enhance IT capabilities and competitiveness.

The Senior Security AI Risk Analyst will assess and secure AI-enabled systems at Sony Interactive Entertainment, identifying material security risks, control gaps, and data classification issues. The role requires translating findings into actionable recommendations, partnering with Responsible AI & Governance and security teams, and maintaining a portfolio view of emerging AI security trends.…See more Candidates must have 6+ years securing technical systems with recent hands-on generative AI experience, strong knowledge of modern AI stacks, and the ability to interrogate designs, trace data flows, and identify security weaknesses in LLM and agentic systems. The position demands both deep security fundamentals (identity, permissions, data protection, monitoring) and a practical builder mindset to use tooling, APIs, and automation to explore and improve systems.

Design and develop performance modeling platforms and tools for Qualcomm's AI/ML hardware accelerators targeting cloud data server applications. Analyze and optimize LLM and AI workloads on SoC architectures, working across hardware architecture, DDR memory controllers, NoC design, and compiler frameworks.…See more Collaborate with multi-disciplinary hardware and systems engineers to find optimal architecture tradeoffs and improve performance and power efficiency. Apply deep expertise in AI workloads, ML frameworks, computer architecture, and RTL design/verification to build systems that validate LLMs and complex ML networks.

Lead and manage a team of IT engineers while driving the design, implementation, and maintenance of IT infrastructure, systems, and applications. Responsibilities include planning scalable and secure IT solutions, collaborating across departments to understand technical requirements, evaluating emerging technologies, establishing engineering standards and procedures, monitoring system performance, and managing vendor relationships.…See more Requires 5+ years of IT engineering experience with a focus on system design and infrastructure management, plus 2+ years in a leadership/managerial role.