Embedded Firmware Engineer

Why Work at Banner?

For over 50 years, Banner Engineering has been at the forefront of industrial automation. We offer products and solutions including award-winning sensors, wireless solutions, machine safety, indication and LED lighting. From Fortune 500 leaders to innovative startups, Banner's award-winning products and solutions are helping companies around the world increase efficiency, reduce costs, safeguard equipment, and protect personnel. Our commitment to innovation shows through a continuous, market-driven evolution of products and technology.

With engineers employed in nearly every major department, engineering is in our DNA.

Banner Engineering is committed to offering competitive pay and benefits, including, but not limited to:

• 401(k) with match
• Student Loan 401(k) match program
• Medical, Dental, and Vision Insurance Plans
• HSA (Health Savings Account) with company contribution
• Paid Time Off (PTO)
• Sales and Profit Sharing Eligibility
• Flexible work hours
• Life Insurance
• Paid Parental Leave
• Pet Insurance

Base Pay Range: $109,341 - $158,331

The estimated range is the budgeted amount for this position. Final offers are based on various factors, including skill set, experience, location, qualifications and other job-related reasons.

We’re looking for a hard-working individual who would like to join us in developing new advanced sensors utilizing novel embedded AI system solutions. The Embedded Firmware Engineer position is a hands-on research and investigative role focusing on product design. This role offers the opportunity to make a meaningful impact in a fast-paced and collaborative environment.

This position reports to the Sr. Technologist.

• Architect, design, and develop software for machine vision systems running on embedded edge AI hardware.
• Participate in end-to-end software development lifecycle, from concept and architecture through implementation, testing, and delivery.
• Optimize software for performance, memory usage, and power efficiency on resource-constrained.
• Design embedded system solutions that are modular, scalable, testable, maintainable, and capable of real-time performance.
• Support system bring-up, low-level debugging, and performance tuning on target hardware platforms.
• Define and maintain software architecture, coding standards, and long-term platform strategy.
• Lead the investigation, design, implementation, optimization, documentation, and characterization of new products and features.
• Collaborate closely with the product owner to define, refine, and implement product requirements.
• Collaborate with cross-functional engineering teams (hardware, firmware, manufacturing, test) to support product development.
• Evaluate and resolve manufacturing and field issues related to software, systems, or product performance.
• Direct product-level testing activities to ensure software quality, robustness, and reliability.
• Provide technical leadership, including training and mentoring of junior engineers.
• Other duties as assigned.

• Bachelor’s degree in Software Engineering, Computer Science, Computer Vision, or a related field
• 8+ years of professional experience in embedded software development
• Programming proficiency in embedded C or C++
• Demonstrated experience with memory optimization and performance tuning on resource-constrained systems
• Experience with machine vision pipelines, including camera interfaces and image processing workflows
• Basic understanding of machine learning and AI fundamentals, particularly as they relate to model deployment and inference on embedded or edge devices

• Master’s Degree in Software Engineering, Computer Science, Computer Vision, or a related field
• Programming competency with Object-Oriented design and programming languages (e.g., C++, Python)
• Non-real time and real-time OS experience, with understanding of multi-threading, inter-process communications, interrupt handlers, and related topics
• Experience implementing and debugging Ethernet-based communication protocols
• Experience deploying AI models using Tensor Flow Lite, ONNX Runtime, or similar on embedded edge AI device
• Experience with…