AI Data Platform/Pipeline Engineer

AI Data Platform / Pipeline Engineer

(Full-time, onsite in El Segundo, CA — U.S. citizenship required due to the nature of our work)

About Cambium

Cambium is an advanced materials startup building next generation polymer and composite systems for aerospace, defense, and critical industries. We combine physics-based modeling, experimentation, and cutting-edge AI—including multimodal foundation models—to accelerate materials discovery and deployment.

Role Summary

We are seeking an AI Data Platform + MLOps engineer to build the pipelines, infrastructure, and automation that powers our AI foundation models, computational chemistry, and operational tools. You will build the data backbone that accelerates foundation model development and drives AI deployment into real manufacturing and operational workflows—with a mandate to reduce friction, eliminate manual pipelines, and enable rapid iteration.

Key Responsibilities

• Build robust pipelines for chemistry, materials, and manufacturing data ingestion and transformation.
• Define data contracts, dataset versioning, and labeling/standardization workflows.
• Operate ETL/training orchestration, experiment tracking, model registry, and deployment automation.
• Manage cloud workflows (Azure + GCP), reproducible environments, monitoring, and cost/performance tuning.
• Connect R&D and Ops systems (ELN/LIMS/ERP/MES) into unified data flows.

Qualifications

• 10+ years in data science, Dev/Ops, MLOps, or data engineering in an operational setting
• Expert data pipelines, data tech stacks, orchestration, and MLOps/DevOps tooling.
• Ability to design resilient, scalable pipelines in ambiguous, fast-moving environments.
• Strong systems thinking, requirements gathering, and cross functional collaboration skills.
• Familiarity with scientific or manufacturing data is a plus.

BENEFITS

Cambium offers a highly competitive compensation and benefits plan. This includes excellent medical/dental/vision benefits, and a matching 401(k) plan, professional development reimbursement, and an opportunity for equity for most full time positions.

As a condition of employment, the candidate may need to successfully complete a medical evaluation and obtain clearance to wear respiratory personal protective equipment (PPE) as required by OSHA 29 CFR 1910.134