Among computer and information research scientists, AI is already used for a large share of the tasks. Measured exposure for computer and information research scientists: 34% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

Our client, an AI-driven startup within the manufacturing industry, is hiring a hands-on Director of AI to join their team in San Jose, CA. The successful candidate will play a key role in shaping the company's AI vision, developing the knowledge graph, agentic systems and machine learning infrastructure that drive intelligent decision-making across global manufacturing operations.

Responsibilities

Lead the design, development and evolution of the company’s AI and machine learning architecture.

Build, deploy and scale production-grade knowledge graph systems that power intelligent decision-making.

Develop advanced AI agents capable of reasoning across complex manufacturing, supply chain and operational datasets.

Create intelligent planning, forecasting and decision-support solutions using real-time data.

Collaborate closely with founders, engineers and customers to transform industry challenges into practical AI-powered products.

Establish and maintain best practices for model development, deployment, evaluation, monitoring and governance.

Support the growth of the AI function by helping to recruit, mentor and develop future AI and machine learning team members.

Skillset

At least 6 years of experience in artificial intelligence, machine learning or applied research, with a strong record of delivering real-world impact.

Master's or PhD in Computer Science, Artificial Intelligence, Machine Learning or similar.

Demonstrate a proven ability to build, deploy and scale AI and machine learning systems in production environments.

Have hands-on experience designing, implementing and managing knowledge graph solutions at scale.

Possess deep expertise in agentic AI, reasoning frameworks, retrieval systems or multi-agent architectures.

Show a strong understanding of modern machine learning infrastructure, MLOps practices and model lifecycle management.

Communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders.

Track record of building and scaling enterprise SaaS products and platforms is a plus.

Exposure to manufacturing, supply chain or industrial technology environments is a bonus.

Benefits

Salary: $160,000–$180,000

Meaningful Equity.

Flexible hybrid working.