Embedded Systems, Audio DSP, Acoustics & Embedded Machine Learning.

Feather Engineering helps companies build modern audio, wearable, and embedded products—combining electronics, firmware, digital signal processing, acoustics, and embedded machine learning. From concept through production-ready hardware and software, we design systems that are efficient, reliable, and tuned for real-world performance.

Let’s Talk About Your Next Device
What We Do

End-to-End Engineering for Audio, IoT & Wearables

Whether you need a complete subsystem designed from the ground up or a specialist to solve a hard signal-processing or machine learning problem, Feather Engineering fits into your team where you need the most help. We’re particularly strong at projects that blend audio, sensing, and embedded intelligence.

Core Capabilities

We design the electronics that make your product possible, with attention to low noise, robustness, and manufacturability.

  • System-level architecture and partitioning
  • Schematic capture and design review
  • PCB layout for analog, digital, RF, and power (2–12+ layers)
  • Low-noise analog front ends and mixed-signal design
  • Prototype bring-up, debug, and validation
  • Documentation and manufacturing handoff

We write firmware that makes your hardware dependable and responsive, from low-level drivers to real-time application code.

  • Bare-metal and RTOS-based firmware for MCUs and SoCs
  • Communication stacks: BLE, WiFi, USB, UART, I²C, SPI
  • Real-time control loops and audio pipelines
  • Shared-memory and inter-core communication (e.g., MCU ↔ DSP frameworks)
  • Bootloaders, update mechanisms, and diagnostics
  • Integration with existing codebases and toolchains

We design and implement DSP algorithms with an emphasis on music and voice performance.

  • Music and voice processing algorithms
  • Filtering, EQ, dynamics, and spectral shaping
  • Voice clarity and intelligibility optimization
  • Low-latency signal chains for real-time use
  • Prototyping and analysis in MATLAB / Python
  • Optimized implementations on DSP cores and MCUs

Feather Engineering brings machine learning out of the lab and into resource-constrained devices. We focus on ML that has to run on-device—low power, limited memory, and real-time.

  • Feature engineering for audio, motion, and sensor data
  • Streaming feature pipelines that combine DSP and ML
  • Model development and training for classification, detection, and event recognition
  • TinyML-oriented architectures for low RAM/Flash devices
  • Experience with TensorFlow Lite / TFLite Micro, PyTorch, and uTFLite

Platforms and Toolchains:

  • ARM Cortex-M33-based MCUs
  • HiFi5 DSP cores and audio SoCs
  • uTFLite on M33 & HiFi5 (current work)
  • Quantized and fixed-point model deployment
  • SIMD-accelerated inference (where available)

The result is embedded ML that is not just a prototype in Python, but tuned and running reliably on your actual hardware.

We bridge electronics, DSP, and real-world acoustics to create systems that actually sound right.

  • Transducer selection and system architecture
  • Enclosure and porting tradeoffs
  • Measurement and characterization of drivers and systems
  • Tuning for tonal balance, loudness, and intelligibility
  • Test fixture and measurement workflow design
  • Support for both lab-grade and production-oriented test setups