--- title: 'Senior/Staff Scientist - Algorithms & Data Products at SirenOpt' canonical: 'https://feeny.ai/job/senior-staff-scientist-algorithms-data-products-sirenopt-san-leandro-gvvg84y0z46z' type: 'job' last_seen: '2026-10-18' --- # Senior/Staff Scientist - Algorithms & Data Products at SirenOpt - **Company:** SirenOpt - **Location:** San Leandro, CA - **Compensation:** $140k–$190k - **Posted:** 2026-10-01 - **Last confirmed live:** 2026-10-18 - **Apply:** https://job-boards.greenhouse.io/sirenopt/jobs/4430493009 ## 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: Senior/Staff Scientist - Algorithms & Data Products Location: On-Site (San Leandro, CA) Job Type: Full-Time ## Role Overview We’re looking for a Senior Scientist, Algorithms & Data Products to join our core R&D team, working at the heart of our manufacturing intelligence platform – not in a commercial analytics role. You’ll turn rich plasma sensor signals into trusted metrics and models and to build the automation that powers our next generation of experiments. In this role you will: - Design and build algorithms that map multi‑modal sensor data (optical emission spectra, electrical signals, thermal/other sensors, process context) into robust “material fingerprints” and properties. - Work with systems, plasma, and applications engineers to marry hardware and software: designing and automating experiment protocols for our benchtop, inline roll‑to‑roll, and robotic piece‑to‑piece platforms. - Shape our first generation of models and metrics for battery electrodes and ceramic barrier coatings, directly influencing what customers see and trust. This is a high‑impact, hands‑on R&D role at the core of SirenOpt’s technology stack, shaping how we design, run, and learn from our experiments. ## What You'll Do - Own end to end modeling pipelines from raw sensor data to customer facing metrics and alerts. - Develop multi modal representations of plasma-material interactions that generalize across different materials, geometries, and processes. - Design and implement automated experimental protocols (parameter sweeps, DOE campaigns, calibration routines) that coordinate plasma hardware, motion/robotics, sensing, and data capture. - Work with embedded, controls, and software engineers to design deployment architectures across edge devices, host controllers, and cloud systems. - Define performance metrics, validation strategies, and monitoring for models running in benchtop products and pilot manufacturing lines. - Own the trustworthiness of our data – interrogate raw and derived data for instrument artifacts, drift and silent pipeline failures, and build the checks that catch a bad result before it reaches a model, a customer metric, a disclosure, or a paper. ## What We're Looking For - Advanced degree (PhD or MS with substantial experience) in a quantitative field such as physics, applied mathematics, statistics, electrical engineering, computer science, or similar, with a strong focus on data analysis and modeling. - 6+ years of hands on experience (industry or postdoc) building models for real world sensor or process data, not just web/NLP/recommender systems. - A track record of catching problems in data that others missed – artifacts, drift, miscalibration, or a pipeline quietly producing plausible nonsense. - Strong Python skills and experience with scientific computing/ML tooling (NumPy, SciPy, pandas, scikit learn; familiarity with PyTorch or similar is a plus). - Demonstrated ability to design and execute end to end analysis workflows: data ingestion and cleaning, feature engineering, model training, validation, and reporting. - Experience with at least one of: spectroscopy, imaging, time series/multivariate process data, or other high dimensional measurement modalities. - Solid grounding in statistics (hypothesis testing, confidence intervals, experimental design, control charts, etc.) and comfort reasoning about uncertainty and robustness. - Experience designing or implementing automated experimental workflows or test rigs that integrate hardware and software (e.g., lab automation, instrument control, hardware in the loop setups, industrial test stands). - Proven ability to communicate technical results clearly, in writing and in person, to both technical and non technical stakeholders. - Comfortable working in lab and/or industrial environments: dealing with noisy data, incomplete logging, and partially instrumented systems. Nice to have: - Comfort working with hardware APIs (e.g., vendor SDKs, REST/gRPC services, serial/fieldbus interfaces) from Python or similar, and reasoning about timing, synchronization, and error handling. - Experience with multi‑modal data fusion (combining spectral, imaging, and process data) or related techniques in domains such as autonomous systems, medical imaging, or industrial inspection. - Background in plasma physics, optical diagnostics, materials science, or related fields - or strong interest and ability to learn these areas quickly. - Experience deploying models into edge or real‑time systems with latency and reliability constraints. - Familiarity with lab automation or experiment orchestration tools (e.g., custom Python control scripts, LabVIEW, PLC/SCADA, or equivalent), and interest in building lightweight, code‑driven alternatives. - Experience with experiment tracking, MLOps, or data‑centric tooling (e.g., MLFlow, Weights & Biases, DVC) and modern software engineering practices (Git, code reviews, CI/CD). - Prior work with battery manufacturing, roll‑to‑roll processes, or high‑temperature coatings (e.g., turbine components) is a strong plus. Base Pay Range $140,000—$190,000 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 ## Other roles at SirenOpt - [Staff Embedded Linux Software Engineer](https://feeny.ai/job/staff-embedded-linux-software-engineer-sirenopt-san-leandro-1tppdmzfax32) — San Leandro, CA - [Software Engineer (Early Career) – C++ & Systems](https://feeny.ai/job/software-engineer-early-career-c-systems-sirenopt-san-leandro-9f5sr9deekkq) — San Leandro, CA - [Senior Technical Sales Engineer](https://feeny.ai/job/senior-technical-sales-engineer-sirenopt-san-leandro-s8972z8mbap1) — San Leandro, CA - [Staff/Senior Mechanical Engineer](https://feeny.ai/job/staff-senior-mechanical-engineer-sirenopt-san-leandro-bd3kk0f6rywc) — San Leandro, CA - [Senior/Staff Software Engineer - C++](https://feeny.ai/job/senior-staff-software-engineer-c-sirenopt-san-leandro-crz4qk56qpbe) — San Leandro, CA - [Metrology Data Scientist](https://feeny.ai/job/metrology-data-scientist-sirenopt-san-leandro-1gc1vjkphztb) — San Leandro, CA - [Staff Quality Engineer](https://feeny.ai/job/staff-quality-engineer-sirenopt-san-leandro-m9sd523ecqth) — San Leandro, CA - [Sr. Account Manager](https://feeny.ai/job/sr-account-manager-sirenopt-san-leandro-9qbnr3f1knwz) — San Leandro, CA - [Senior Product Manager](https://feeny.ai/job/senior-product-manager-sirenopt-san-leandro-pn0r0t6ax8xj) — San Leandro, CA - [Metrology Applications Engineer](https://feeny.ai/job/metrology-applications-engineer-sirenopt-san-leandro-rq9dwz4cdbdp) — San Leandro, CA