Artificial Intelligence Jobs in Berkeley, CA

The Engagement Manager will drive customer adoption of AI solutions, ensure successful deployments, and build strong relationships with enterprise clients to achieve transformational value with AI tools.

The Enterprise Account Executive will develop relationships with key decision-makers at Fortune-class enterprises, drive sales growth, and deliver solutions for voice call management to enhance customer experience.

Lead cross-functional teams to design and deliver commercial analytics projects for life sciences clients. Provide strategic guidance, analyze data, develop actionable insights, manage client communications and timelines, build/optimize data processes (including coding and visualization), support business development, and mentor junior staff.

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

As an Applied AI Engineer, design and build intelligent AI systems, manage data ingestion layers, and ensure security while scaling AI infrastructure.

The Product Designer will drive product design, engage in user research, create design deliverables, and collaborate closely with teams to shape innovative enterprise products.

The Principal Architect will lead the technical direction of low-code applications, defining architecture, guiding engineers, and ensuring governance and best practices for scalable solutions.

As an Applied AI Engineer, you'll drive the development of AI-powered financial products, collaborating across teams to build and improve systems, optimizing generative AI applications, and contributing to foundational model applications.

The Head of Data & AI will architect and operationalize a data-driven future, shaping the AI-first data strategy and managing the data ecosystem from architecture to governance and activation to drive business intelligence and automation.

Drive technical sales and customer success for AI companies, owning implementation and providing effective solutions for usage-based billing.

The IT and AI Readiness Coordinator role involves stakeholder engagement, process analysis, and data readiness for AI transformation in business operations.

As an AI Application Engineer, build and deploy Agentic AI applications for Fortune 500 companies, analyze customer requirements, and enhance the GenAI performance.

Build and maintain scalable backend services and APIs, optimize system performance, collaborate with stakeholders, and improve AI workflows.

As a Staff Data Scientist II, you'll develop AI-driven monetization strategies and lead the design of scalable machine learning systems, collaborating across teams to innovate ad technology.

Lead sales efforts for AI solutions at Labelbox, developing relationships with top AI labs and Fortune 500 companies, managing the sales cycle and ensuring client satisfaction.

The AI Engineer role involves optimizing language models for fraud detection and building backend infrastructure to support scalable operations for risk management and as well as developing efficient machine learning solutions.

As an AI Platform Backend Engineer, you'll design and deploy backend systems utilizing AI for real-world applications, optimize performance, and mentor junior engineers while working directly with clients to address complex challenges.

As an AI Platform Engineer, you will design and develop AI-driven backend solutions, optimize performance, and collaborate with customers and teams.

You will build frameworks for LLM-powered agents, design reinforcement learning approaches, lead development of scalable evaluation systems, and mentor other engineers while writing robust code for enterprise-grade assistants.

The AI Engineer will develop scalable AI systems, optimize LLMs, maintain data workflows, and ensure system resilience while collaborating on innovative solutions.

As an AI/ML Platform Engineer, you will develop APIs, data pipelines, and workflows to support AI capabilities for scientific research, ensuring system reliability and scalability.

The Lead Product Manager, AI will identify and build AI-powered products, drive growth and customer experience, and collaborate with cross-functional teams.

As a Full-Stack Engineer at Labelbox, you will develop and maintain AI tools, focusing on data training systems, intermediate user interfaces, scalable architectures, and work in a collaborative, fast-paced environment.

The AI Enablement Engineer leads programs for engineering teams to integrate AI, teaches best practices, and develops scalable learning models.

The ML Software Engineer will design and develop scalable backend services for AI/ML workflows, focusing on data engineering and system reliability.