Artificial Intelligence Jobs in Oakland, CA

Lead AI initiatives, establish strategy, and develop generative AI applications. Collaborate with teams to build and optimize financial products.

Lead 0→1 product development for Emerald Cloud Services: define vision, conduct customer discovery, set product requirements for AI compute provisioning and management, partner with engineering and GTM teams, and launch and scale cloud services for enterprise and AI customers.

Interns will work with the AI Machine Learning and Data Science Team to build machine learning models and provide data-driven insights, collaborating with product and engineering teams.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

As an AI Product Engineer, you will develop and deploy AI-driven software solutions, collaborate with customers, and optimize applications for real-world impacts.

The AI/ML Engineer will design and deploy advanced AI models, optimize performance, and directly engage with government officials to transform industries through innovative AI solutions.

Embed with customers to learn their workflows, redesign and build production GenAI/LLM systems on AWS, ship and operate code, evaluate non-deterministic models, and own business outcomes.

The Sales Strategy and Operations Manager leads complex sales opportunities, develops ROI models, engages executives, and coordinates cross-functional input for compelling proposals.

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 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.

Own the design-for-manufacturing software layer of the Matter Compiler CAM stack. Develop computational geometry algorithms, manufacturability constraints, layout and retention logic, physical process models, validation systems, and production knowledge bases. Collaborate with AI, modeling, design, and process engineering teams to translate manufacturing expertise into auditable, testable code and validate results against fab runs.

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%).

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.

The AI-Native Data Engineer will build data pipelines, architect databases, design GCP infrastructure, and automate workflows for energy management using AI.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

As an AI Engineer, you'll lead backend implementation, build AI-powered products, and ensure high-quality systems, contributing to Elicit’s tech stack and user experience.

Lead technical strategy and execution for Merlin's AI Core platform across perception, sensor fusion, planning, and control. Build and manage a multidisciplinary engineering organization, own architecture from data pipelines to real-time onboard inference, enforce aviation-grade safety and quality, partner with certification and systems teams, recruit senior talent, and translate research into product opportunities.

Lead strategy, architecture, delivery, and operations of enterprise AI platforms and AI-enabled solutions. Define roadmap, build reusable AI capabilities, deliver production-grade generative and agentic AI, establish AI-native engineering practices, ensure responsible AI governance, and partner with cross-functional stakeholders to scale AI adoption and measure business impact.

Build and test AI-enabled prototypes, internal tools, prompts, and agentic automations. Translate requirements into small software components, write basic unit tests, support prompt engineering and API integrations, document designs and runbooks, participate in code reviews and demos, and follow data privacy, security, and responsible AI practices while learning SDLC and team processes.

Founding research hire to develop clinical reasoning and computer-use models using proprietary hospital and clinic data. Own end-to-end training and evaluation pipelines, design benchmarks exposing LLM weaknesses on clinical reasoning, run experiments, and publish technical reports and papers. Collaborate closely with founders and deploy research into products that improve physician workflows.

The Senior Staff AI Engineer will lead the design and optimization of reinforcement learning systems for enterprise applications, focusing on scalable architectures and production deployment. Responsibilities include mentoring, collaboration, and ensuring compliance with AI ethics and safety standards.

Develop and prototype AI-driven applications, validate ideas with real data, and transition projects into production while collaborating with teams and customers.