Role & responsibilities:

This role sits at the intersection of hardware, sensors, and AI models at DigiInfra Agentic AI. You will build the capture stack for dashcam units, stand up NVIDIA Jetson Orin nodes, and integrate thermal and LiDAR sensors, working closely with the AI team and Hardware Engineering Manager. This is a hands-on role in a small team - time at the bench with a soldering iron and logic analyser, time in a terminal cross-compiling and profiling inference, and time in the field debugging installations.

Key result areas

- Edge device bring-up: bring up and maintain edge compute nodes (NVIDIA Jetson, ARM SBC) - OS/BSP setup, peripheral enablement, boot/storage configuration, reproducible flashing images.
- Sensor integration & calibration: integrate RGB, thermal, LiDAR, depth, IMU and GPS sensors into working capture pipelines, including driver integration, calibration and time synchronisation.
- On-device model deployment: take trained models from the AI team and deploy them on edge silicon within latency/power budgets using ONNX and TensorRT, including quantisation and benchmarking.
- Device software & connectivity: build and maintain the on-device application layer - capture scheduling, local buffering, GPS tagging, health telemetry, cloud upload and OTA updates.
- Field deployment & reliability: take devices from bench to field - power budgeting, thermal management, enclosure/ingress considerations, mounting, installation support and on-site debugging.
- Documentation & handover: wiring diagrams, setup runbooks, calibration procedures and BOM inputs.

Role details
- Designation: Embedded Systems Engineer - Edge AI & Sensors (alternate title: Edge AI Engineer / Embedded Perception Engineer)
- Function: Hardware Engineering, reporting to the Hardware Engineering Manager
- Base location: Bangalore, with 10-20% travel for field deployments and installations across India
- Experience: 2-5 years in embedded Linux, edge AI or sensor systems
- Employment type: Full time, on-roll





Preferred candidate profile

Essential

- 2+ years hands-on experience in embedded Linux, edge AI deployment or sensor systems engineering
- Proficient in Python and C++, comfortable working inside an inference pipeline
- Comfortable on embedded Linux on ARM (JetPack or Yocto/Debian based images), systemd services, device tree basics, cross-compilation, kernel modules and driver troubleshooting
- Working knowledge of hardware interfaces: I2C, SPI, UART, GPIO, USB3, MIPI CSI-2, Ethernet, with debugging using a multimeter, logic analyser or oscilloscope
- Practical experience with camera/video pipelines: V4L2, GStreamer, RTSP, encoding and frame timing
- Experience deploying trained neural networks to edge devices (ONNX Runtime, TensorRT), including quantisation and latency benchmarking
- Git and structured version control habits, with strong documentation discipline
- Willingness to travel for field deployments and work outdoors at installation sites

Preferred (nice-to-have)
- Direct NVIDIA Jetson experience (Orin Nano/NX/AGX) and familiarity with DeepStream
- Thermal imaging experience (FLIR, Lepton or similar), including radiometric data and calibration
- LiDAR integration (Livox, RPLIDAR, Ouster or similar), point cloud handling and sensor fusion with camera data
- Multi-sensor time synchronisation (PTP, PPS, GPS-disciplined timing, hardware triggering)
- Camera-LiDAR extrinsic calibration and IMU integration
- Hailo, Coral or other NPU accelerator SDK experience
- ROS 2 experience (nodes, topics, bag recording)
- Power budgeting, battery/solar systems, thermal design, IP-rated enclosure selection
- MQTT, Azure IoT Hub or equivalent device-to-cloud telemetry and OTA frameworks
- Ability to read schematics and carrier board layouts; KiCad or Altium familiarity
- Experience with unattended, low-bandwidth or remote deployments

Perks and benefits
- Compensation commensurate with experience, finalised at offer stage
- Hands-on ownership across hardware, sensors and AI on real-world edge deployments

📌 Embedded Systems Engineer (Bengaluru)
🏢 DigiInfra AI
📍 Bengaluru