Metrology Data Scientist

About SirenOpt

SirenOpt helps manufacturers make better, safer, and more reliable micro- and nano-materials. These materials are the building blocks of critical sectors of the global economy such as batteries, computer chips, aircraft components, and power systems. But, surging material demand and growing complexity are pushing production to unprecedented scales and speeds, leaving manufacturers effectively flying blind. Small, undetected variations during production lead to wastage, lower performance, higher costs, and safety risks.

SirenOpt is changing this by developing a manufacturing intelligence platform that non-destructively probes materials during production, revealing critical internal information without damaging them. Using a novel combination of cold atmospheric plasma, physics-informed machine learning, and predictive analytics, SirenOpt generates unique, real-time material fingerprints that capture material signals not accessible through conventional measurement techniques. These insights give manufacturers unprecedented visibility into how materials behave as they are made.

We turn hidden data into actionable intelligence to help manufacturers reduce variability and thus increase yield and performance. The technology can be deployed as a standalone tool or integrated directly into factory production lines. SirenOpt is currently deploying early versions of its platform with some of the largest industrial manufacturers in the world across North America, Europe, and Asia.

About the job

Job Title: Metrology Data Scientist – Signal Modeling & Applied Metrology

Location: On-Site (San Leandro, CA)

Job Type: Full-Time

Role Overview

We are seeking a Metrology Data Scientist to join our Applications Engineering team. In this role, you will build and deploy machine learning models that turn complex, high-dimensional sensor signals into actionable predictions about material properties, bridging the gap between raw instrument data and manufacturing intelligence.

This is a forward-deployed, customer-adjacent role. You will work directly with customer samples and datasets to execute proof-of-concept studies, validate model performance on novel materials, and translate results into product improvements. You will collaborate closely with software and hardware engineering teams to move models from research into production.

What You'll Do

Model Development & Calibration

• Build, calibrate, and validate predictive models that map sensor signal features to material properties

• Design and evaluate new model architectures and featurization strategies suited to small-data, high-dimensional scientific datasets