Firmware Engineer - Camera

Mill is all about answering a simple question: how can we prevent waste? Less waste can save time, money, energy, maybe even our planet. And there’s no better place to start than food. Food waste is one of the most solvable climate problems facing us today. Plus, our trash really stinks. It’s gross, heavy, and our least favorite chore. At Mill we are striving to build a better environment for all, as we take on climate and kitchen change.

We are seeking an extraordinary Firmware Engineer to lead the vision system development for our next-generation product. You will evaluate SoC and MCU platforms, and develop camera-based AI applications for object detection (either on-device or cloud-based). Collaborating closely with hardware designers, connectivity experts, and system engineers, your work will be crucial in turning innovative concepts into functional prototypes and products.

Key Responsibilities

• Evaluate, benchmark, and select SoC/MCU platforms suitable for vision workloads and potential cloud integration.
• Prototype and deploy vision pipelines: capture raw image frames, perform preprocessing (ISP, color conversions), and manage AI inference models either locally or via cloud services.
• Collaborate with hardware teams to select optimal image sensors, lenses, and camera modules for object detection and classification tasks.
• Implement low-level drivers (I²C/SPI, GPIO, PWM) and incorporate them into device trees and board-support packages.
• Work with other team members to define and implement inter-processor communication protocols (SPI/UART/I²C) for sensor data exchange and system telemetry.
• Ensure coexistence of camera subsystems with other embedded peripherals (touchscreen, motors, sensors, connectivity modules) without performance degradation.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related discipline, or equivalent experience.
• 5 years experience in embedded firmware engineering, including at least 3 years focused on camera or vision applications.
• Strong proficiency in C/C (Linux kernel drivers or RTOS firmware), with knowledge of memory management, DMA, interrupts, and real-time system constraints.
• Hands-on experience with camera interfaces: MIPI-CSI-2, USB Video Class (UVC), or parallel RGB; comfortable working with image sensor datasheets, register programming, and sensor configuration.
• Familiarity with vision frameworks (OpenCV, TensorRT, TensorFlow Lite, Edge TPU) or cloud-based AI processing platforms (AWS, Azure, Google Cloud); capable of prototyping object detection or segmentation pipelines, profiling performance, and suggesting optimizations.
• Solid understanding of I²C, SPI, UART, and GPIO interfaces.
• Proven prototyping ability—quickly translating high-level performance targets into functional prototypes and effectively evaluating hardware-software tradeoffs.
• Skilled in using logic analyzers, oscilloscopes, and debugging tools (JTAG, GDB) to troubleshoot camera issues.
• Excellent communication skills, capable of producing clear documentation, architecture diagrams, and engaging in effective cross-team collaboration.

Preferred Skills

• Experience with camera calibration techniques, including lens distortion correction and color-space conversions.
• Experience with integrating touchscreen panels (LVDS/DSI/HDMI) and touch controllers (I²C/SPI), and developing responsive user interfaces.
• Develop and optimize embedded UI frameworks (e.g., Qt Embedded, LVGL).
• Familiarity with Linux system architectures, cross-compilation, build systems, and kernel module integration.
• Experience with OTA firmware updates for MCUs (bootloaders) and SoCs (partition management).
• Previous experience in startups or rapid prototyping environments.
• Familiarity with Agile methodologies, version control (GitHub), CI/CD pipelines, and project management tools (JIRA).

The estimated base salary range for this position is $170k to $225k, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.