As a Forward Deployed Engineer IV for GenMedia at Google Cloud, you will embed with strategic enterprise customers to architect, build, and deploy production-grade generative media solutions using Google's frontier multimodal AI models (video, image, audio). You'll move beyond high-level design to hands-on coding and debugging, solving critical production blockers around integration, data readiness, and state management while serving as a feedback loop for Google Cloud's product roadmap.… The role requires 8+ years shipping AI-driven solutions in Python, C++, or TypeScript, with direct experience architecting scalable systems using generative models, ensuring data sovereignty and GDPR compliance, and leading technical discovery with executive stakeholders. You'll combine deep technical expertise with a founder's mindset to deliver bespoke, high-fidelity AI systems that drive business outcomes for leading enterprises and creative organizations.
model-governance jobs in San Diego
Build and ship production ML systems end-to-end for autonomous medical coding in a SaaS platform, from problem framing through deployment and monitoring. Own the full lifecycle—data discovery, feature engineering, training, evaluation, and iteration—working with LLMs, deep learning, and modern MLOps tooling to handle millions of medical charts daily.… Design robust, low-latency architectures, establish rigorous evaluation strategies, and implement model observability, drift detection, and bias assessments. Collaborate across product, data, and platform teams to translate business goals into measurable ML outcomes.
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.… 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.
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).… 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.
Lead the design, development, and operation of Qualcomm's enterprise AI platform, supporting agentic AI, model lifecycle management, and multi-cloud ML/inference infrastructure. Own core platform services including identity/RBAC, secrets, service meshes, observability, vector stores, and model gateways across on-prem GPU clusters and managed cloud services.… Manage a ~10-engineer global team (platform, SRE, MLOps/LLMOps), drive incident response and continuous improvement, and partner with product and security teams on AI governance and high-impact use cases.
Staff engineer leading architecture and evolution of Qualcomm's Ambient Perception Platform for always-on, context-aware AI on power-constrained edge devices. Responsibilities include designing low-power AI runtime platforms, multimodal sensing systems, secure data architectures, and heterogeneous computing frameworks across Android, Linux, Windows, XR, automotive, and IoT.… Requires 4+ years software engineering experience (or equivalent with advanced degree), 2+ years with C, C++, Java, or Python, and expertise in embedded systems, ARM/DSP/NPU optimization, and edge AI workload efficiency. Strong preference for 8–12+ years in software architecture, platform frameworks, and heterogeneous SoC development.