Customer Engineer (AI)

TL;DR

Customer Engineer (AI): Deploying AI models trained on physical sciences and connecting them to autonomous labs to solve materials and process engineering problems with an accent on technical trust, problem scoping, and industrial integration. Focus on building data pipelines, translating messy industrial data into AI inputs, and bridging the gap between AI research and real-world factory deployments.

Location: On-site in Menlo Park, California. Preference for candidates located in Menlo Park or San Francisco.

Compensation: $300,000–$400,000 per year

Company

AI and physical sciences company building state-of-the-art models to accelerate breakthroughs across materials, energy, and advanced manufacturing.

What you will do

• Embed with customer engineering and R&D teams on-site in fabs and factory floors to understand critical technical problems.
• Scope and frame problems that map onto AI models, lab capabilities, or data pipelines.
• Own end-to-end delivery from problem definition and data ingestion to model runs and results interpretation.
• Build and adapt technical integrations including data pipelines, API connections, and model inference workflows.
• Translate messy industrial data (process records, equipment logs) into clean inputs for AI models and LIMS.
• Serve as the technical face to customers, presenting results to engineering leads and executives to build long-term partnerships.

Requirements

• BS/MS/PhD in materials science, chemical engineering, mechanical engineering, physics, or a closely related field.
• Hands-on software engineering ability with proficiency in Python, APIs, and databases.
• Experience working with industrial or scientific data such as process logs and equipment telemetry.
• Proven ability to work directly with technical stakeholders and earn their trust.
• Comfort operating in high-ambiguity, high-ownership situations.
• Willingness to travel regularly and work on-site at customer facilities, including cleanrooms and factory floors.

Nice to have

• Experience in forward-deployed or field engineering roles at an industrial AI company.
• Domain depth in semiconductor process engineering, aerospace, battery/energy materials, or advanced manufacturing.
• Familiarity with AI/ML workflows, training pipelines, and model evaluation.
• Experience with LIMS, MES, ELN, or industrial data infrastructure (SCADA, OPC UA).
• Background in experiment design (DOE) or statistical process control.

Culture & Benefits

• Opportunity to be the first hire of this kind in a rapidly growing frontier AI company.
• High-ownership environment where you define the playbook for customer deployment.
• Collaboration with world-class scientists and engineers.
• Visa sponsorship is provided.