Artificial Intelligence Jobs in Oakland, 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.

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.

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.

The role involves applying diffusion techniques and developing AI models to enhance 3D reconstruction pipelines for various industries.

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.

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.

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.

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.

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

As an Embodied AI / Simulation Engineer, you will develop manipulation systems for robotics, focusing on simulation, machine learning, and real-world implementation. Your responsibilities include designing training policies, maintaining simulation environments, and deploying models to robotic systems.

The Corporate AI Engineer develops and operationalizes AI solutions across the enterprise, ensuring compliance and optimizing performance while working closely with various teams.

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

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 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.

Lead Data Scientist responsible for creating ML-driven risk assessments and AI workflows within a SaaS security platform, ensuring effective decision-making and system reliability.

The Senior AI Applications Engineer provides post-deployment support for AI solutions, ensuring high performance and customer satisfaction through technical expertise and problem-solving.

As an AI Analyst, you'll research the AI landscape and create impactful content for CIOs, synthesizing complex information into persuasive narratives to help drive executive decisions.

Design, ship, and scale production-grade AI systems, integrating LLMs with focus on reliability, safety, and performance. Collaborate across teams and mentor engineers.

Design, ship, and scale multi-agent systems, integrate LLMs and multimodal models, optimize AI workflows, and ensure production readiness in a hands-on engineering role.

The Product Manager will evaluate and manage relationships with LLM models, define product strategy, and coordinate cross-functionally to enhance customer experience while driving product roadmap and adoption.

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