SirenOpt is accelerating sustainable and smart manufacturing of advanced materials using intelligent characterization and real-time decision-making to drive the creation of innovative, high-performance products that fuel the advancement of society. Backed by Activate Venture Partners.
About the role
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. Found on 1752vc Careers, the job board for startup and VC roles.
What they'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
More about this role
At SirenOpt®, we are building the manufacturing intelligence layer for advanced materials. We help manufacturers visualize, understand, and control the material behavior that determines yield, performance, and safety across energy, aerospace, automotive, electronics, and semiconductor applications.
We are working on this problem because advanced materials are becoming more critical and more complex, but the tools used to manufacture them have not kept pace. Manufacturers still lack real-time visibility into the small variations that shape quality on the line. We care because those invisible variations cause scrap, waste energy and materials, create higher costs, inconsistent product performance, and introduce avoidable safety risks.
We developed PlasmaSens™, our manufacturing intelligence platform, to close that visibility gap and to lay the foundation for truly autonomous manufacturing.
We are uniquely suited to solve this problem because our expertise and our platform connect material science, plasma physics, machine learning, and manufacturing in one system. The same core technology works in-line, at-line, and off-line, and across form factors ranging from electrodes and wafers...
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