Senior/Staff Scientist - Algorithms & Data Products
About this role
SirenOpt builds a manufacturing intelligence platform that non-destructively probes micro- and nano-materials during production to generate real-time material fingerprints. The core R&D team seeks a Senior or Staff Scientist to transform rich plasma sensor signals into trusted metrics and models while automating the next generation of experiments. The person in this role will design algorithms mapping multi-modal sensor data, build end-to-end modeling pipelines, and collaborate with hardware engineers to deploy solutions for battery electrodes and ceramic barrier coatings. Ideal candidates possess a strong quantitative background, hands-on experience with real-world sensor or process data, and a practical mindset for working in lab or industrial environments.
What you will do
- Design and build algorithms that map multi-modal sensor data into robust material fingerprints and properties.
- 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 that coordinate plasma hardware, motion or robotics, sensing, and data capture.
- Define performance metrics, validation strategies, and monitoring for models running in benchtop products and pilot manufacturing lines.
- Interrogate raw and derived data for instrument artifacts, drift, and silent pipeline failures to ensure data trustworthiness.
What you need
- Hold an advanced degree such as a PhD or MS with substantial experience in a quantitative field like physics, applied mathematics, statistics, electrical engineering, or computer science.
- Bring six or more years of hands-on industry or postdoc experience building models for real-world sensor or process data.
- Demonstrate strong Python skills alongside experience with scientific computing and machine learning tooling such as NumPy, SciPy, pandas, and scikit-learn.
- Show a proven ability to design and execute end-to-end analysis workflows encompassing data ingestion, cleaning, feature engineering, model training, validation, and reporting.
- Possess experience with at least one high-dimensional measurement modality including spectroscopy, imaging, or time-series and multivariate process data.
- Maintain a solid grounding in statistics with comfort reasoning about uncertainty, robustness, and experimental design.
- Demonstrate experience designing or implementing automated experimental workflows or test rigs that integrate hardware and software.
Nice to have
- Comfort working with hardware APIs from Python and reasoning about timing, synchronization, and error handling.
- Experience with multi-modal data fusion or related techniques in domains such as autonomous systems, medical imaging, or industrial inspection.
- Background or strong interest in plasma physics, optical diagnostics, or materials science.
- Experience deploying models into edge or real-time systems with latency and reliability constraints.
- Familiarity with lab automation, experiment tracking, MLOps, or data-centric tooling and modern software engineering practices.
Benefits
- Equity and salary compensation depending on experience
- Health, Dental, and Vision plans provided
- 401k matching provided
- 20 days of PTO per year
- Approximately 15 paid US holidays per year
Skills and tech stack
Questions candidates ask
Where is this role located?
The position is an on-site role located in San Leandro, California.
What is the salary range for this position?
The base pay range is $140,000 to $190,000 USD, with equity and salary compensation depending on experience.
What kind of technical background is required?
Candidates need an advanced degree in a quantitative field and at least six years of hands-on experience building models for real-world sensor or process data using strong Python skills.
What time off benefits are included?
Employees receive 20 days of PTO per year, plus approximately 15 paid US holidays per year.