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
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
Skills Required
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field
- 0-2 years of professional software development experience, including applicable internships, co-ops, research, or substantial personal/open-source projects
- Solid foundation in C++, including memory management, references, pointers, the standard library, object-oriented programming, and generic programming
- Strong ability to read, understand, and write Python in existing automation, testing, and data analysis codebases
- Ability to learn and modify programming languages beyond C++ and Python
- Understanding of data structures, algorithms, operating systems, and concurrency fundamentals
- Familiarity with Linux command-line tools, build systems such as CMake, debuggers, and Git-based development workflows
- Hands-on experience using AI coding tools such as Claude Code, GitHub Copilot, or Cursor, with ability to review and test generated output
- Comfort working with lab and test equipment, sensors, real hardware, and data collection for testing and validation
- Clear written and verbal communication and ability to collaborate across disciplines
- 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 Ethernet, USB, or Serial hardware communication interfaces
- Contributions to open-source projects
What We Do
SirenOpt is accelerating sustainable and smart manufacturing of advanced materials by delivering a manufacturing intelligence platform that uses intelligent characterization and real-time decision-making to drive the creation of innovative, high-performance products that fuel the advancement of society. SirenOpt is pioneering a paradigm shift in materials manufacturing intelligence by leveraging cold atmospheric plasma, machine learning and predictive analytics to non-destructively create a uniquely distinctive, multifaceted material fingerprint in real-time. SirenOpt transforms measurement blind spots into rich multi-layered material insights, which enable intelligent performance-centric decision-making. SirenOpt thus accelerates R&D and process optimization, enhances product performance, and delivers higher production quality to maximize value in both in-line and off-line applications. SirenOpt’s manufacturing intelligence platform has demonstrated use cases across battery, aerospace, semiconductor, electronic and many other advanced manufacturing segments in both inline production and offline tool deployments. SirenOpt was founded in 2022 as a spin-out from the UC Berkeley Chemical Engineering Department. SirenOpt is supported by the UC Berkeley Skydeck, Lawrence Berkeley National Laboratory Cyclotron Road and Activate science-driven startup accelerator programs. For employment opportunities please visit our careers page: https://www.sirenopt.com/careers
