Artificial Intelligence Jobs in Berkeley, CA

Lead strategy and development of AI and technology products, managing cross-functional teams to enhance legal workflows and compliance standards.

The role involves building AI platform capabilities, mentoring engineers, collaborating with teams, and scaling systems for large datasets as part of a legal tech transformation.

Lead end-to-end delivery of enterprise AI engagements: run discovery, size value, define features, coordinate cross-functional teams, drive adoption and change management, and own commercial expansion and program outcomes in regulated environments.

Develop and train large-scale multimodal foundation models (vision and language) that fuse imaging with molecular data, build scalable distributed ML pipelines for petabyte-scale datasets, and collaborate with experimental scientists and engineers to productionize models and systems.

Lead applied research on continual learning, fast adaptation, memory, and transfer learning for agentic systems. Own end-to-end pipeline from data generation to evaluation and product integration, run experiments, produce code, and drive research strategy while mentoring and managing a small team.

Lead applied research on spatial reasoning, geometric and physical world modeling. Own data generation, evaluation, and product integration. Implement experiments, build production code, and drive research strategy in 3D, multimodal, simulation, and related domains.

Develop and productionize agentic engineering systems for a physical-world AI agent. Build and maintain the agentic harness and tool integrations, run evaluations, analyze production traces, debug failures, collaborate with research to create and deploy custom models, and incorporate new agentic frameworks into the product.

Partner with attorneys to identify workflow pain points and design, build, and integrate AI solutions and agentic workflows. Implement prompt-engineered applications, integrate with M365/iManage/EDW, iterate with stakeholders, document deliveries, and monitor LLM innovations.

Build and scale AI data and ML infrastructure: evaluation systems, fine-tuning pipelines, agent-first product surfaces, high-throughput data workflows, and integrations of new models into production.

Own the full QA lifecycle for AI-powered legal solutions: design and run unit, integration, system, performance, and scalability tests; integrate automated suites into Azure DevOps CI/CD; generate and evaluate AI-assisted test cases; maintain defect tracking and quality metrics; collaborate with security and engineering teams to ensure production-ready releases.

Embed with enterprise customers to deploy production agentic AI workflows: integrate data sources, identity, CRMs and APIs; handle security, SSO/SCIM, isolated VMs and compliance; drive adoption, instrument usage, and feed product improvements to scale deployments.

Embed with enterprise customers to design, build, and deploy production agentic AI workflows. Integrate platform with customer systems, handle security and compliance reviews, drive adoption and expansion, and feed product improvements based on field signal.

Lead product marketing for Procore AI & Data products: own positioning, messaging, launches, competitive positioning, sales enablement, and cross-functional GTM programs. Collaborate with Product, Demand Gen, Sales, and global Marketing to create customer-facing content and drive adoption.

Lead AI-focused internal audits and investigations to detect misuse, fraud, compliance violations, and insider threats in AI systems. Develop methodologies, analytics, continuous monitoring, and control assessments; supervise auditors; partner with Legal, Security, Privacy, and business stakeholders; and deliver risk-based findings and remediation recommendations.

Lead engineering delivery and operational health of corporate platforms (Workday ecosystem), owning integrations, security and AI enablement. Define multi-year roadmaps, build scalable AI agents and governance, set analytics/data strategy, and lead multidisciplinary teams to modernize platforms across HR, Finance, and GBS.

Lead and support AI-focused audits, investigations, and advisory reviews to detect misuse, fraud, and compliance violations. Analyze AI systems, logs, prompts, outputs, and access patterns; perform data analytics to identify anomalies; document findings and evidence; conduct stakeholder interviews; develop audit observations, playbooks, and remediation follow-up. Collaborate with technology, compliance, legal, HR, and security teams and maintain audit independence and professional skepticism.

This role involves driving new client acquisition and revenue growth through full-cycle sales execution and relationship building with stakeholders, while maintaining pipeline tracking in CRM.

Lead development and implementation of the firm's attorney AI learning strategy. Assess training needs, design curricula, credentialing, and workshops; coordinate cross-functionally with KM, IT, and practice leaders; track participation and outcomes; monitor legal AI tools and translate developments into practical lawyer-facing training and guidance.

Lead architecture and implementation of agentic AI systems powering Zuma's platform. Rebuild onboarding and integration frameworks, implement analytics and observability for LLM performance, translate product needs into technical solutions, mentor engineers, establish engineering standards, and work directly with customers to enable scalable, production-grade AI experiences.

Lead end-to-end development and production deployment of agentic AI systems and full-stack products. Architect integrations with property management systems, improve reliability and observability, define engineering standards, and partner with product and operations to ship scalable AI agents across voice, text, and email.

Lead identification, prioritization, and implementation of AI-driven use cases and automation across global programs. Drive POCs, design future-state workflows, gather requirements, build governance, create AI-enabled dashboards and playbooks, partner with IT/vendors, and train teams to increase adoption and operational efficiency.

Lead AI product strategy and execution for MISUMI Americas' manufacturing quoting and fulfillment platform. Define AI vision, own model lifecycle and infrastructure, build AI-driven features (automated quoting, supplier recommendation, manufacturability assessment), set metrics and experimentation, and align cross-functional partners to operationalize models at scale while championing responsible AI and mentoring other product managers.

Seeking Machine Learning Systems Engineers to build end-to-end 3D native ML systems, focusing on training and inference challenges.

The AI Infrastructure Engineer designs, develops, and optimizes core capabilities for the AI inference platform, focusing on reliability, scalability, and operability of infrastructure and services.

The Director of AI Product Management at WatchGuard will drive the strategy and execution of an AI-powered action layer, manage the product roadmap, collaborate cross-functionally, and ensure value delivery to MSP partners.