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

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$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