Metrology Data Scientist

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

Apply methods including regression, dimensionality reduction, probabilistic modeling, anomaly detection, and physics-informed ML

Model Validation & Production Readiness

Develop testing and validation frameworks for model performance, including uncertainty quantification and out-of-distribution detection

Characterize model robustness across sample types, process conditions, and instrument configurations

Prepare models and documentation for handoff to the software engineering team for production deployment

Customer-Facing Proof-of-Concept Work

Analyze datasets from customer proof of concepts

Compile technical reports and supporting materials to deliver to customers

Translate findings and stakeholder feedback into model improvement roadmaps

What We're Looking For

B.S. in Data Science, Statistics, Applied Mathematics, or a related quantitative science field with 3-5 years of applied ML/data science experience; or M.S. with 1-3 years (Ph.D. a plus, not required)

Hands-on experience building and validating predictive models (supervised and self-supervised) in Python

Ability to analyze multivariate, high-dimensional datasets and perform feature engineering and selection

Solid grasp of statistical modeling: uncertainty quantification, regularization, covariate analysis, and feature importance methods

Strong communicator; comfortable presenting technical findings to both technical and non-technical audiences

Nice to have:

Experience working with time-series, spectroscopic, or other sensor-based signal data

Prior work in manufacturing, materials science, energy storage, semiconductors, or another physical science domain

Prior customer-facing or applications engineering experience in a technical product company

Experience deploying models in production software environments

Familiarity with data pipeline development (PostgreSQL or similar)

Fluency in Mandarin Chinese, Japanese, German, Korean, or another key stakeholder language

Base Pay Range

$120,000—$170,000 USD

Benefits

• Equity and Salary compensation depends on experience
• Health, Dental, Vision plans provided
• 401k matching provided
• Time off: 20 days of PTO per year, plus approximately 15 paid US holidays per year