Lead Embedded Linux Engineer
JOB DESCRIPTION
Top 3 reasons to join us
- Competitive salary
- Full statutory insurance
- Professional, international working environment
Job description
About Safetrust
Safetrust is building the future of identity. Imagine a world where your phone, wearable, or digital credential becomes your secure key—unlocking buildings, systems, and experiences seamlessly across physical and digital environments. That’s what we do.
Our platform combines IoT devices, mobile credentials, and cloud-native architecture to power secure access for Fortune 200 companies and global enterprises. As we evolve from a hardware-centric model to a platform and services-driven business, marketing plays a critical role in shaping how the market understands—and adopts—Safetrust.
About the role:
The Embedded Linux Engineer is responsible for building secure, reliable, and scalable embedded platforms for Safetrust's identity and access products, including a growing line of vision-enabled devices that combine camera pipelines with on-device AI inference. This position plays a key role in the embedded engineering team, ensuring our devices are fast, secure, and field-ready.
This role focuses on technical leadership, architecture, and hands-on execution across the stack — from board bring-up and kernel optimization to camera integration, edge AI acceleration, secure boot, and OTA updates — and contributes to Safetrust's continued growth by strengthening the reliability and intelligence of our physical access control hardware.
Key Responsibilities:
- Develop and maintain Linux-based firmware for custom embedded hardware platforms.
- Work on bootloaders (U-Boot, Barebox, etc.), kernel configuration, and device drivers — including camera (V4L2, MIPI CSI) and sensor drivers.
- Integrate and optimize open-source software stacks for secure and real-time applications.
- Build and tune on-device camera and computer-vision pipelines (GStreamer, OpenCV, V4L2) for streaming, capture, and real-time analytics.
- Deploy and accelerate AI/ML models on edge hardware — quantize, prune, and integrate models via TensorRT, OpenVINO, TensorFlow Lite, ONNX Runtime, or vendor NPUs (e.g. Hailo, NVIDIA Jetson, Rockchip NPU, Ambarella).
- Enable secure OTA updates, encryption, key management, and remote diagnostics.
- Collaborate closely with hardware, AI, security, and backend teams to ship complete solutions.
- Analyze and resolve performance, stability, and integration issues across the camera-to-inference path.
- Support manufacturing and QA teams with tooling and debugging aids.
- Lead the embedded Linux team technically — set coding standards, run design and code reviews, mentor engineers, and own technical decisions across the product line.
Your skills and experience
Skills & Experience:
- 5+ years of experience in embedded Linux development, with at least 2 years at senior level.
- Minimum 2 years of experience as a technical lead — driving architecture decisions, owning a product or major subsystem end-to-end, running code reviews, and mentoring 2+ engineers.
- Strong knowledge of kernel and user-space programming, especially in C/C++.
- Hands-on experience with bootloaders, device trees, Yocto/OpenEmbedded or Buildroot.
- Hands-on experience with camera integration on Linux: V4L2, MIPI CSI, ISP tuning, GStreamer pipelines, and at least one of OpenCV or a comparable CV framework.
- Working experience deploying AI/ML inference on edge devices — model conversion, quantization, and runtime integration with at least one of TensorRT, OpenVINO, TensorFlow Lite, ONNX Runtime, or a vendor NPU SDK.
- Familiarity with secure boot, trusted execution environments (TEE), and encryption fundamentals.
- Solid grasp of low-level interfaces: SPI, I2C, UART, GPIO, USB, Ethernet, MIPI.
- Ability to read schematics and collaborate effectively with hardware engineers.
- Comfortable with Git, CI/CD pipelines, and Linux shell scripting.
- Strong written and spoken English for cross-office collaboration with US and Australia teams.
Nice to Have / Preferred
- Experience with HSMs, secure elements, or PKI in embedded contexts.
- Experience with BLE, Wi-Fi, NFC, or UWB stack integration.
- Hands-on experience with specific edge AI platforms: Rockchip NPU, Qualcomm QCS.
- Experience with face detection / recognition pipelines, person detection, or other computer-vision use cases relevant to physical access control.
- Familiarity with model optimization techniques: INT8 quantization, pruning, knowledge distillation, layer fusion.
- Experience formally line-managing engineers (1:1s, performance reviews, growth planning).
Success Profile:
The ideal candidate is:
- Deeply technical and hands-on, comfortable moving between kernel, driver, and AI/inference layers.
- A natural technical leader who mentors engineers and sets high engineering standards.
- Methodical about security and reliability in embedded systems.
- Able to own architecture decisions end-to-end and drive them to production.
- Comfortable working across regions and functions in a global environment (Vietnam, US, Australia).
Why you'll love working here
- Competitive salary based on experience and performance
- 13th-month salary
- Daily lunch is provided at the office
- Free coffee, tea, and refreshments
- Full statutory insurance (social, health, unemployment)
- Annual health check-up and paid annual leaves
- Professional, international working environment