Staff Electrical Engineer

Responsibilities

• Lead the architecture, design, implementation, and validation of FPGA, MPSoC, and FPGA-based digital signal processing systems
• Develop designs from concept through RTL development, modeling, simulation, and system bring-up
• Build and maintain robust simulation and verification environments
• Design and implement FPGA-based digital signal processing pipelines for real-time sensing
• Implement and refine signal-processing and control algorithms such as PID and ADPLL
• Use MATLAB and Python for algorithm development, modeling, and data analysis
• Collaborate with hardware, software, and systems engineers for end-to-end integration
• Troubleshoot and debug hardware/firmware interactions using lab equipment

Requirements

• B.S., M.S., or PhD in Electrical Engineering, Computer Engineering, or a related field
• 5+ years of relevant industry experience
• Strong experience with end-to-end FPGA and MPSoC design
• Advanced experience with FPGA-based digital signal processing for real-time systems
• Proficiency in algorithm modeling using MATLAB and Python
• Strong command of HDL/RTL implementation
• Hands-on experience with testbenches and verification environments
• Ability to read electrical schematics and work at the board level
• Proven experience troubleshooting hardware in a lab setting

Preferred Qualifications

• Technical leadership experience for hardware and firmware teams
• Experience with image processing or vision-related algorithm pipelines
• PCB design experience and familiarity with signal integrity
• Experience with high-speed interfaces or instrumentation systems
• Familiarity with mixed-signal systems (ADCs, DACs, sensors)

Benefits

• Equity and salary compensation based on experience
• Health, Dental, and Vision plans
• 401k matching
• 20 days of PTO per year
• Approximately 15 paid US holidays per year

About the Company

SirenOpt helps manufacturers make better, safer, and more reliable micro- and nano-materials using a manufacturing intelligence platform that combines cold atmospheric plasma, physics-informed machine learning, and predictive analytics.