Novus Hi-Tech - Software Engineer - ADAS/Device Driver

2 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Position Summary

We're building safety first video telematics products (ADAS/DMS/driver behavior analytics) that run efficiently on edge devices inside commercial vehicles.You will write modern C++ software, integrate and optimize CV/ML pipelines, and ship reliable, low latency perception features such as driver monitoring and distance estimation from camera feeds.

Key Responsibilities

  • Own C++ software modules for on device video capture, preprocessing, inference, and post processing on Linux.
  • Implement classical image processing pipelines (denoise, resize, color space, undistortion) and CV algorithms (keypoints, homography, optical flow, tracking).
  • Build and optimize distance/spacing estimation from monocular/stereo camera(s) using calibration, geometry, and/or depth- estimation networks.
  • Integrate ML models (PyTorch/TensorFlow - ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone- usage, smoking, seat belt, etc.
  • Hit real time targets (FPS/latency/memory) on CPU/GPU/NPU using SIMD/NEON, multithreading, zero copy buffers.
  • Write clean, testable C++, CMake builds, and Git based workflows (branching, PRs, code reviews, CI).
  • Instrument logging/telemetry; debug with gdb/addr2line, sanitize and profile with perf/valgrind.
  • Collaborate with data/ML teams on dataset curation, labeling specs, training/evaluation, and model handoff.
  • Work with product & compliance to meet on road reliability, privacy, and regulatory expectations.

Qualifications

  • B.Tech/B.in CS/EE/ECE (or equivalent practical experience).
  • 2-3 years in CV/ML or video- centric software roles.
  • Hands on in modern C++ on Linux, with strong Git and CMake.
  • Solid image processing and computer- vision foundations (camera models, intrinsics/extrinsics, distortion, PnP, epipolar geometry).
  • Practical experience integrating CV/ML models on device (OpenCV + ONNX Experience building real time pipelines for live video (GStreamer/FFmpeg, RTSP/RTMP, ring buffers), optimizing for latency & memory.
  • Competence in multithreading/concurrency, lock free queues, and producer-consumer designs.
  • Comfort with debugging & profiling on Linux targets.
Reporting To : Technical Lead ADAS

Requisites

  • Experience with driver monitoring or ADAS features; event logic and thresholding for production alerts.
  • Knowledge of monocular depth estimation, stereo matching, or structure from motion for distance estimation.
  • Model training exposure (PyTorch/TensorFlow): augmentation, evaluation (precision/recall, ROC/PR), quantization/pruning, conversion to ONNX/TensorRT/NCNN.
  • Hardware acceleration (GPU/VPU/NPU, Arm NEON/DSP), YOLO/RT DETR/Lightweight backbones on edge.
  • Cross compiling, Yocto/Buildroot, containerized toolchains; unit tests (gtest), static analysis (clang tidy, cppcheck), sanitizers.
  • Basic familiarity with MQTT/IoT, message schemas, and over the air updates.

Technical Competency

  • Languages: C++, Python
  • CV/ML: OpenCV, ONNX Runtime/TensorRT/NCNN/MediaPipe; PyTorch/TensorFlow (for training/eval).
  • Video: GStreamer/FFmpeg, V4L2, RTSP/RTMP.
  • Build/DevOps: CMake, Git, gtest, clang- tidy, sanitizers; CI/CD (GitHub/GitLab/Bitbucket).
  • Debug/Perf: gdb, perf, valgrind
(ref:hirist.tech)

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