Artificial Intelligence Jobs in Fremont, CA

Own and evolve Jerry.ai's AI platform: consolidate prompts from six locations onto a unified system, prioritize chatbot technical work, drive architecture and emerging-technology decisions (voice/computer use), manage the OpenAI relationship, and coordinate cross-functional teams to deliver scalable production-grade AI features while keeping current systems running.

Lead development and consolidation of Jerry.ai's AI agent platform, owning roadmap to rollout. Design prompt strategies, evaluation frameworks, guardrails, and API/system architecture. Partner with engineers and OpenAI to deploy voice and workflow automation, drive experiments to improve automation rates, accuracy, and customer satisfaction, and establish AI best practices across the org.

The role involves designing and developing high-performance web apps, improving user interfaces, maintaining component libraries, and ensuring code quality through comprehensive testing and collaboration with other teams.

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.

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.

Part-time AI Application Engineer focused on measuring and improving healthcare AI agent performance in production. Responsibilities include instrumenting agent quality, identifying failure points, designing experiments, analyzing results, and partnering with clinical experts to improve patient outcomes. The role requires Python, strong analytical judgment, comfort with ambiguity, and interest in healthcare. Clinical experience is valued but not required. Engagement is structured as a paid internship or contract role with weekly Bay Area office syncs.

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.

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.

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.

Own full sales and partnership cycle to bring voice AI to mobile service robots: engage senior robotics decision-makers, qualify and prioritize opportunities, close deals, and shape the commercial playbook while operating autonomously within a small technical team.

Lead technical engagements with robotics customers to design and integrate voice AI into mobile robots, own POCs and technical evaluations, clear deployment roadblocks, collaborate with sales/product/services, and feed customer learnings into the product. Travel across Europe for onsite evaluations (20–30%).

Join a VC-backed startup network connecting Director/VP-level AI/ML leaders to portfolio companies. Lead AI strategy, build and scale ML teams, deploy and improve production ML systems, set model quality and responsible AI standards, partner with product and engineering, oversee data and MLOps, evaluate models and tooling, and communicate strategy to executives and boards.

Join a talent network connecting senior/staff applied AI scientists to VC-backed startups. Responsibilities include researching and developing ML methods, fine-tuning foundation models, designing experiments and evaluation frameworks, building prototypes, collaborating with engineering/product to productionize models, improving model robustness and efficiency, curating datasets, investigating failures, mentoring peers, and communicating results to stakeholders.

Join a talent network connecting Principal AI/ML Engineers with VC-backed startups. Responsibilities include architecting and deploying production ML/DL models, researching state-of-the-art methods (LLMs, transformers, RL), building scalable training/inference pipelines, implementing robust MLOps, optimizing model performance, and leading technical strategy and teams.

Join a talent network connecting founding AI engineers with VC-backed startups. Responsibilities include designing, building, and deploying ML/DL models, creating scalable data pipelines, optimizing real-time and batch model deployments, developing RAG and LLM systems, and aligning AI strategy with founders and product goals.

Lead and manage a team delivering advanced AI/HPC and data center infrastructure solutions. Oversee planning, budgeting, solution design, pre-sales technical support, vendor enablement, reference architectures, KPI reporting, documentation, and cross-functional collaboration to ensure successful deployment of GPU‑accelerated compute, networking, storage, and facility solutions.

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.

Embed with business teams to identify workflows, rapidly prototype, and deliver production AI applications using LLMs, agents, RAG, and enterprise integrations. Build full-stack solutions, integrate with platforms (Microsoft 365, Salesforce, Oracle), deploy to cloud, and create reusable AI components and standards to drive enterprise adoption and measurable business value.

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 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.

The Software Engineer will develop backend systems for an AI Energy Agent, including data integration, microservices, and scalable architecture, focusing on performance and reliability.