Careers at Sirenopt

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: Software Engineer (Early Career) – C++ & Systems Location: On-Site (San Leandro, CA) Job Type: Full-Time Role Overview SirenOpt is seeking a Software Engineer to help build and maintain the real-time data pipeline behind our sensing platform: acquiring data from multiple sensors, processing and storing it on Linux-based systems, and delivering it to the applications our customers rely on. You will work primarily in modern C++ and Python, with mentorship from senior engineers, and you will be hands-on with real hardware in our lab to test and validate what you build. This is a role for someone who wants to grow into a well-rounded systems engineer by shipping production software end to end, from a first design discussion to a feature running at a customer site. What You'll Do Develop and maintain software components in modern C++ (C++17/20) for Linux-based systems, with guidance from senior engineers Implement features, fix bugs, and write unit and integration tests across the data pipeline, from sensor acquisition through processing and storage to the services that deliver results to applications Write and maintain Python scripts for automation, testing, and data analysis Read, and where needed modify, existing code written in other languages across our codebase Use AI coding tools (e.g., Claude Code, GitHub Copilot) to accelerate development, and verify their output through testing, profiling, and code review Run the system on real hardware in the lab to test and validate your changes, including setting up sensors and collecting data Participate in code reviews, both receiving and giving feedback, and follow team conventions for code quality Help diagnose and debug issues across software and hardware boundaries, working with firmware and hardware engineers Measure and improve performance of existing code under the direction of senior engineers Document your work so that others on the team can build on it What We're Looking For Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (recent graduates welcome) 0–2 years of professional software development experience; internships, co-ops, research, and substantial personal or open-source projects count Solid foundation in C++, including memory management, references and pointers, the standard library, and basic object-oriented and generic programming Strong ability to read, understand, and write Python, including working within existing Python codebases used for automation, testing, and data analysis Ability to pick up new programming languages quickly; our codebase spans several languages and you will need to read, and occasionally modify, code outside of C++ and Python Understanding of core computer science fundamentals: data structures, algorithms, operating systems, and concurrency basics Comfortable with the everyday toolchain: Linux command line, build tools (CMake or similar), a debugger, and Git-based workflows (branches, pull requests, code review) Hands-on experience using AI coding tools (e.g., Claude Code, GitHub Copilot, Cursor) as part of a real development workflow, and the judgment to review and test what they produce Comfortable working hands-on with lab and test equipment: setting up sensors, running the system on real hardware, and collecting data for testing and validation (we will train you on our specific equipment) Clear written and verbal communication, and the ability to work well with teammates across disciplines Nice to have: Experience with Qt, gRPC, or Protocol Buffers Familiarity with CI/CD pipelines and automated testing Experience with profiling and debugging tools such as perf, Valgrind, GDB, or sanitizers Familiarity with hardware communication interfaces such as Ethernet, USB, or Serial Contributions to open-source projects What You'll Learn You will work on a real-time sensing platform that is already running at some of the largest manufacturers in the world, on a small team where your code reaches customers quickly. How a high-throughput, multi-sensor data pipeline is built end to end, from acquisition through processing and storage, and kept reliable in production Modern C++ and Linux systems engineering, with regular code review and mentorship from senior engineers How software, firmware, and hardware teams work together to ship a physical product How to use AI coding tools effectively and responsibly in a professional engineering workflow A clear path to grow into a mid-level engineer with ownership of your own components Base Pay Range $120,000 — $160,000 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 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 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 Software Engineer - C++ Location: On-Site (San Leandro, CA) Job Type: Full-Time Role Overview SirenOpt is seeking a Senior / Staff Software Engineer to design and build the high-performance C++ and systems software that powers our manufacturing intelligence platform. In this role, you will help ensure the reliability, performance, and scalability of SirenOpt's software as it runs on real customer production lines, while contributing to the architecture and technical foundations needed for a growing commercial product. Working closely with firmware, hardware, and application engineering teams across every phase of product development, you will design and optimize multi-threaded, asynchronous software on Linux, analyze and improve performance across CPU, memory, storage, networking, and I/O, and debug complex issues that span software and hardware boundaries. You will also read, maintain, and extend existing Python tooling used for automation, testing, and data analysis, and take ownership of software components throughout the full product development lifecycle. This position is well suited for a self-driven engineer who takes ownership of their work, writes clean and maintainable modern C++ (C++17/20), and enjoys understanding how software interacts with operating systems and hardware to achieve exceptional performance. You will contribute at a high level in a collaborative, fast-moving engineering environment, participating in architecture, technical design, and code reviews as you help ship robust software for commercial products. What You'll Do Design, develop, and optimize high-performance software using modern C++ (C++17/20) Develop scalable, reliable, and maintainable software for Linux-based systems Design multi-threaded and asynchronous software architectures Analyze, profile, and optimize software performance across CPU, memory, storage, networking, and I/O Read, understand, maintain, and enhance existing Python code used for automation, testing, and data analysis Collaborate closely with firmware, hardware, and application engineering teams Participate in software architecture, technical design, and code reviews Debug complex system-level issues across software and hardware boundaries Take ownership of software components throughout the product development lifecycle What We're Looking For The ideal candidate is passionate about building high-quality commercial software and solving challenging systems problems. You take ownership of your work, write clean and maintainable code, and enjoy understanding how software interacts with operating systems and hardware to achieve exceptional performance. Experience building and shipping software for commercial products is highly valued. You thrive in a collaborative environment and enjoy working across software, firmware, and hardware disciplines to build products used in real customer environments. Required Qualifications Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field 5+ years of professional software development experience (Senior) or 8+ years (Staff) Strong proficiency in modern C++ (C++17/20) Working knowledge of Python with the ability to read, understand, maintain, and modify existing Python code Strong experience developing software on Linux Strong understanding of: Operating systems, Memory management, Multi-threading and concurrency, Software architecture, Performance optimization Excellent debugging and problem-solving skills Experience using Git and modern software development workflows Nice to have: Experience designing and developing large-scale commercial software systems Experience developing and shipping software for commercial products Experience with scientific instrumentation or data acquisition systems Experience collaborating with firmware and hardware engineering teams Familiarity with low-latency, real-time, or data acquisition software systems Experience developing desktop applications using Qt Widgets and Qt Charts Familiarity with scientific computing, signal processing, physics, or machine learning Experience with Linux systems programming Experience with performance profiling tools such as perf or Valgrind Experience with CMake and GDB Familiarity with Embedded Linux Experience with hardware communication interfaces such as Ethernet, USB, PCIe, or Serial Familiarity with CI/CD and automated testing Base Pay Range $160,000 — $240,000 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 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 Systems Engineer Location: On-Site (San Leandro, CA) Job Type: Full-Time Role Overview We are seeking a Staff Systems Engineer to define, integrate, and validate SirenOpt's plasma-based sensing platform for deployment into advanced manufacturing environments. As an early-stage member of the SirenOpt team, you will play a key role in shaping system-level behavior and ensuring technical coherence across hardware, software, and experimental domains, helping establish a strong and scalable technical foundation for the company. This role carries responsibility both for system-level technical ownership and for shaping how technical work is documented across the organization. You will define and evolve the structure used to document experiments, system designs, interfaces, and technical decisions, ensuring clarity, consistency, and traceability as the company grows. These documentation practices are expected to be tightly coupled to hands-on engineering work, including experimentation, data analysis, and system validation. The ideal candidate applies sound systems engineering judgment to complex, cross-disciplinary problems and is comfortable operating in areas of ambiguity. You will drive system-level trade studies, guide experimental strategy, and resolve non-trivial integration and performance issues, while remaining deeply engaged in day-to-day technical execution. This role offers an opportunity to operate at a high level of technical impact in a collaborative and fast-moving engineering environment. What You'll Do Define and own system-level architecture, integration, and validation of SirenOpt's plasma-based sensing platform Guide system-level technical decisions through experimentation, data analysis, and cross-disciplinary evaluation Lead investigation and resolution of complex system performance issues through structured experimentation, data analysis, and root cause analysis Establish and evolve the structure used to document experiments, system designs, interfaces, and technical decisions across the organization Ensure technical documentation is clear, consistent, and traceable, and tightly integrated with hands-on engineering and validation activities Work closely with cross-functional engineering teams to guide system integration and resolve non-trivial cross-disciplinary issues Incorporate customer and application feedback into system-level design evolution and validation strategy Support on-site installation, validation, and system upgrade activities at customer sites as needed Domestic and international travel of approximately 10-15% is expected. What We're Looking For B.S. in Engineering or Physics with 5+ years of relevant industry experience, M.S. with 3+ years, or Ph.D. with 2+ years of hands-on systems experience Experience developing automated metrology, inspection, or diagnostic systems across system definition, integration, validation, deployment, and customer support Experience working in early-stage or ambiguous R&D environments, using experimentation and data analysis to evaluate concepts and guide system-level decisions Proficiency with tools such as Python, MATLAB, C, LabVIEW, or similar for data analysis, modeling, and evaluation of system performance Extensive hands-on experience developing, integrating, and validating prototypes, subsystems, and complete systems Experience working across mechanical, electrical, software, and experimental domains to resolve complex integration and performance issues Demonstrated ability to guide technical direction through experimentation, data-driven analysis, and cross-disciplinary evaluation Experience establishing or evolving technical documentation practices, ensuring clarity, consistency, and traceability of experimental results and system decisions Strong written and verbal communication skills, particularly in documenting complex technical work clearly for diverse audiences Nice to have: Experience with manufacturing metrology equipment and sensors used for characterization or fabrication of advanced materials Experience with requirements and test management tools (e.g., Jama or similar) and data analysis software such as JMP Experience with early-stage R&D and/or new product introduction (NPI) in complex technical systems Exposure to high-precision, high-throughput industrial systems for material handling, metrology, or process automation Prior work or research experience in one or more of the key industrial markets that SirenOpt addresses, including batteries, semiconductors, power generation, energy, or electronics Familiarity with high-voltage devices; exposure to plasma-based systems Experience with capital equipment designed for integration into manufacturing environments, particularly roll-to-roll and piece-to-piece processes Base Pay Range $150,000 — $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 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: Staff Electrical Engineer – FPGA / MPSoC Systems & Digital Signal Processing Location: On-site (San Leandro, CA) Job Type: Full-time Role Overview SirenOpt is looking for a Staff Electrical Engineer – FPGA / MPSoC & Digital Signal Processing Systems to lead the architecture, design, implementation, and validation of high-performance programmable logic, embedded processing, and FPGA-based digital signal processing systems powering our next-generation metrology platform. This is a hands-on, high-impact role for someone who enjoys working close to the technology, solving hard problems quickly, and helping shape products in an early-stage startup environment. This role is ideal for an engineer who is energized by deep tech, thrives in cross-functional environments, and is motivated by the opportunity to build something genuinely new. You will work closely with a small, highly capable team to turn advanced sensing, digital signal processing, and control concepts into robust, high-performance, field-ready systems. What You’ll Do Lead the architecture, design, implementation, and validation of FPGA, MPSoC, and FPGA-based digital signal processing systems for SirenOpt's metrology platform. Develop designs from concept through architecture definition, RTL development, modeling, simulation, verification, testbench development, bench testing, and system bring-up. Build and maintain robust simulation and verification environments to validate functionality, timing, performance, and reliability at both block and system levels. Design and implement FPGA-based digital signal processing pipelines for real-time sensing and metrology applications, including FIR filters, synchronization pipelines, control loops, and low-latency data paths. Implement, evaluate, and refine signal-processing and control algorithms such as PID, ADPLL, filtering, and signal-conditioning methods for high-performance measurement systems. Use MATLAB and Python for algorithm development, modeling, data analysis, system validation, and signal and electrical data characterization. Perform large-scale data analysis to evaluate signal quality, characterize system behavior, and guide design tradeoffs and performance optimization. Collaborate closely with hardware, electrical, software, algorithm, and systems engineers to support end-to-end FPGA, MPSoC, firmware, and hardware integration. Read and interpret schematics to understand board-level architecture, interfaces, signal paths, power domains, and subsystem dependencies. Bring up new boards in the lab, troubleshoot issues independently, and debug hardware/firmware interactions using oscilloscopes, logic analyzers, signal generators, power supplies, and related lab equipment. Help translate frontier R&D concepts into scalable, reliable, and manufacturable digital systems. What We’re Looking For B.S., M.S., or PhD in Electrical Engineering, Computer Engineering, or a related field, with 5+ years of relevant industry experience. Strong experience with end-to-end FPGA and MPSoC design, including architecture, RTL development, simulation, synthesis, timing closure, verification, and board bring-up. Advanced experience with FPGA-based digital signal processing for real-time systems, including FIR filters, synchronization methods, streaming pipelines, and control-oriented digital design. Strong experience with algorithm modeling and analysis using MATLAB and Python. Experience implementing and validating signal-processing and control techniques such as PID, ADPLL, filtering, and signal characterization workflows. Strong command of HDL/RTL implementation for digital signal processing, control, and high-performance data-path design. Hands-on experience developing testbenches, verification environments, and bench-level validation workflows. Strong understanding of firmware/hardware integration and system-level debugging in tightly coupled digital platforms. Ability to read and understand electrical schematics and work effectively at the board and subsystem level. Proven experience troubleshooting and bringing up hardware in the lab using standard electrical test equipment. Experience working in a fast-moving, multidisciplinary environment with a high degree of ownership and technical independence. Strong communication skills and a practical, problem-solving mindset. Nice to Have Experience providing technical leadership for hardware and firmware engineering teams in complex product development environments. Experience with image processing or vision-related algorithm pipelines. PCB design experience, including familiarity with board-level layout considerations and signal integrity tradeoffs. Experience with high-speed interfaces, instrumentation systems, or real-time sensing platforms. Familiarity with mixed-signal systems and integration with ADCs, DACs, sensors, and embedded processors. Exposure to metrology systems, scientific instrumentation, or advanced materials applications. Base Pay Range $180,000 — $220,000 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