---
title: 'Metrology Data Scientist at SirenOpt'
canonical: 'https://feeny.ai/job/metrology-data-scientist-sirenopt-san-leandro-1gc1vjkphztb'
type: 'job'
last_seen: '2026-10-18'
---

# Metrology Data Scientist at SirenOpt

- **Company:** SirenOpt
- **Location:** San Leandro, CA
- **Compensation:** $120k–$170k
- **Posted:** 2026-10-01
- **Last confirmed live:** 2026-10-18
- **Apply:** https://job-boards.greenhouse.io/sirenopt/jobs/4430491009

## Job description

## 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

- 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

## About SirenOpt

## Company Overview
- **One-liner**: SirenOpt provides a non-destructive, real-time materials characterization platform that uses cold atmospheric plasma and AI to create detailed material fingerprints for manufacturing quality control.
- **Entity Type**: Private (Venture stage; total funding $21.5M)
- **Headquarters**: San Leandro, California, United States
- **Founded**: 2022
- **Founders**: Jared O’Leary (CEO), Ali Mesbah (CTO, UC Berkeley), Joel Paulson (co-founder, UW–Madison)

## Core Business
- **Primary Industry**: Manufacturing intelligence / advanced materials characterization (battery, semiconductor, aerospace, medical devices, packaging, electronics)
- **Target Customers**: B2B, Enterprise manufacturers with high-throughput production lines (roll-to-roll, piece-to-piece)
- **Mission**: “Create a paradigm shift in advanced materials characterization by leveraging cold atmospheric plasma, machine learning and predictive analytics to non-destructively create a uniquely distinctive, multifaceted material fingerprint in real-time.” [sirenopt.com](https://www.sirenopt.com/about)

## Products & Services
- **PlasmaSens™** – A modular, scalable platform for inline and offline material analysis. Uses cold atmospheric plasma to measure multiple material properties (e.g., cathodes, anodes, separators, coatings) non-destructively and in real time. Available as a benchtop standalone system, piece-to-piece (robot-arm mounted) for inline inspection, and roll-to-roll (up to 1.5m width) for continuous high-throughput monitoring. Delivers pass/fail feedback and enables predictive quality control. [sirenopt.com](https://www.sirenopt.com/)

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total funding **$21.5M** across five rounds (Pre-Seed $3.0M led by SkyDeck Berkeley, Seed $6.6M led by Visionaries Tomorrow and Voyager Ventures, Venture $6.5M led by Hitachi Ventures and InMotion Ventures, Grant $2.4M from California Energy Commission) [linkedin.com](https://www.linkedin.com/company/sirenopt) [cbinsights.com](https://www.cbinsights.com/company/sirenopt)
- **Notable Investors/Partners**: Voyager Ventures, Visionaries Tomorrow, Hitachi Ventures, InMotion Ventures, SkyDeck Berkeley, California Energy Commission (BRIDGE Grant), Lawrence Berkeley National Lab Cyclotron Road, Activate
- **Growth Signals**: 41 employees (59% technical), deploying with largest industrial manufacturers across North America, Europe, and Asia; first commercial product scheduled for 2026; announced deployment at ECF in Autumn 2026 [sirenopt.com](https://www.sirenopt.com/) [linkedin.com](https://www.linkedin.com/company/sirenopt)

## Competitive Advantages
- **Unique technology**: The only non-destructive measurement method using cold atmospheric plasma to generate a rich, multi-property material fingerprint in real time, without chemicals or sample preparation.
- **Speed**: From hours to seconds – quality decisions made at production speed, catching defects before they propagate.
- **Physics-informed AI**: Combines plasma signals with machine learning to detect hidden defects and predict failure modes, providing insights conventional testing cannot.
- **Flexibility**: Modular platform (benchtop, inline, roll-to-roll) adaptable to diverse substrate sizes and production environments.

## Strategic Focus
- **Commercialization**: Accelerating deployment of PlasmaSens into factory production lines, with a first commercial release in 2026 and an inline deployment at ECF that autumn.
- **Market expansion**: Targeting battery, semiconductor, aerospace, medical device, and packaging manufacturers globally.
- **Sustainability**: Enabling smarter manufacturing to reduce waste, improve yield, and accelerate development of advanced materials. [sirenopt.com](https://www.sirenopt.com/about)

## Why Work Here
- **Impact**: Join a deep-tech startup at the forefront of manufacturing intelligence, working on a “new to the world” metrology tool that transforms how materials are measured and controlled.
- **Engineering culture**: 59% of the team holds technical roles (specialist/senior level); the company values hands-on work in hardware, firmware, software, and AI.
- **Benefits**: Incentive stock options, comprehensive health coverage (medical, dental, vision), 20 days PTO, 15 paid company holidays, and 401(k) matching for qualified employees. [sirenopt.com](https://www.sirenopt.com/careers)
- **Location**: Based in San Leandro, CA (Bay Area). Office presence expected; remote/hybrid policy not explicitly stated.
- **Growth trajectory**: Early-stage (41 employees, $21.5M funding) with active hiring (5 open roles including Lead Software Engineer, Staff EE, Quality Manager) and strong backing from top-tier investors.

## Sources
1. [sirenopt.com](https://www.sirenopt.com/) – Product details, company overview
2. [sirenopt.com/about](https://www.sirenopt.com/about) – Mission, leadership, investors
3. [sirenopt.com/careers](https://www.sirenopt.com/careers) – Benefits, job openings
4. [linkedin.com/company/sirenopt](https://www.linkedin.com/company/sirenopt) – Employee count, funding rounds, department breakdown
5. [cbinsights.com/company/sirenopt](https://www.cbinsights.com/company/sirenopt) – Funding details, product differentiators

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