Artificial Intelligence Jobs in Berkeley, CA

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.

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 Social Media Intern at Inception, you will manage social content across platforms, engage with AI discussions, participate in product launches, and create engaging video content. Aimed at students with a passion for AI and strong writing skills, the role offers direct access to the founding team and the potential for full-time conversion.

Full-cycle technical recruiter responsible for sourcing, screening, and closing AI/ML and computational biology talent. Build candidate pipelines, run first-round technical screens, design interview frameworks, manage ATS data, represent the company at conferences, and partner with founders on hiring strategy and offers including salary and equity negotiations.

Develop prototypes, PoCs, and MVPs for GenAI solutions. Apply deep learning and ML principles using Python, Hugging Face, LangChain, OpenAI API, TensorFlow/Keras/PyTorch, and cloud model services. Work with multi-modal data and intelligent agent tools. Be self-motivated, collaborative, and focused on solving hard AI/GenAI problems.

Lead AI technical strategy, architect AI systems, set safety standards, mentor engineers, and evaluate AI models at Midi Health, a healthcare-focused company.

You will design and build LLM-powered features, integrate AI capabilities into workflows, and contribute to internal practices at a healthcare-focused company.

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

Design and build multi-agent AI systems and RAG pipelines, orchestrate LLMs and embeddings, develop scalable full-stack (Node.js/Next.js) APIs, optimize infra (SQL, AWS/GCP, Docker/K8s), lead technical design-to-deployment, ensure code quality, and implement video content classification and tagging for influencer marketing.

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.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

Lead the go-to-market strategy for an AI-powered product, oversee product releases, collaborate with teams, and drive market positioning.

Design and implement high-performance graphics systems and pipelines for 3D generative AI products. Optimize rendering kernels and geometry processing on GPUs, integrate production-quality pipelines with data and model infrastructure, ensure scalability across GPU clusters and cloud, and collaborate with artists, ML researchers, and product teams. Contribute tooling, documentation, demos, and open-source work to advance Meshy's graphics capabilities.

Build and optimize end-to-end 3D ML systems: training frameworks, high-throughput distributed training across large GPU clusters, custom Triton/CUDA operators, data-loading libraries, and efficient multi-stage inference pipelines with model optimization (compilation, fusion, quantization). Collaborate with researchers on model architecture and maintain production inference endpoints.

Design, build, and operate LLM-facing backend services and evaluation systems. Develop prompts, context pipelines, tool-calling workflows, and retrieval systems. Measure and improve model grounding, consistency, latency, and cost. Ship production-ready solutions and rigorous regression/evaluation pipelines for real-world therapeutic data.

Design, develop, and maintain generative AI and cloud-based AI solutions using Microsoft Azure and Power Platform tools. Collaborate with cross-functional teams to gather requirements, build scalable AI applications, deploy and manage models with Azure Machine Learning, test/debug, document designs, and provide training and user support.

The Technical Product Manager will lead product direction, interface with engineering teams, and ensure the successful deployment of AI-powered safety systems. Responsibilities include defining product vision, translating customer needs, and maintaining high product quality.

You will build and maintain AI-native application features, working with a team of AI and backend engineers to ensure quality and innovation.

Design, build, and deploy production-ready AI solutions across enterprise platforms. Implement LLM workflows (prompt engineering, embeddings, RAG), integrate with enterprise data and SaaS systems, ensure operational readiness (monitoring, logging, performance), and partner with Security, Privacy, IT, and business teams to meet governance and compliance requirements.

Lead enterprise AI strategy and adoption across MISUMI Americas. Build and manage an AI team and champion network, define governance and vendor/platform strategy, prioritize AI use cases, enable adoption through training and resources, measure business impact, and communicate progress to executive leadership. Embed with business teams to move prototypes to production and scale AI-driven workflow automations.

Build and prototype state-of-the-art large language model systems and deep AI assistants, take services from ideation to production, fine-tune and compare open-source and commercial LLMs, use cloud platforms, analyze model and projection accuracy, and collaborate cross-functionally.

Provide embedded legal counsel to product and engineering on privacy, IP, and consumer protection; lead Arena's global privacy program (GDPR, CCPA/CPRA, cross-border transfers); advise on AI governance and responsible deployment; support commercial contracts and data flow frameworks; build privacy processes, playbooks, internal agents, and legal-tech integrations to scale operations.

Lead global strategic partnerships across cloud, GPU, and hardware providers. Identify and negotiate commercial agreements, manage key partner relationships, align cross-functional stakeholders, build business cases, and support executive strategy to enable Higgsfield's AI infrastructure scale and growth.

Own and scale the Nx-based monorepo, build system, and CI/CD to make builds, tests, and developer workflows fast, reliable, and observable. Build developer tooling, local dev stacks, and production-grade developer infra with SLOs, on-call, and measurable DX improvements.