Computer Vision Systems Developer

Type: [Full-Time]

Your Mission

As a Computer Vision Systems Developer, you will be the critical link between AI research and real-world hardware. You won't just train models; you will make them run blazingly fast in production. Your primary focus will be optimizing, deploying, and maintaining robust vision pipelines on [edge devices / cloud infrastructure / robotic platforms] to ensure our systems operate flawlessly in real-time.

The Tech Stack
Languages: Python, modern C++ (C++14+)
Frameworks: PyTorch or TensorFlow, OpenCV
Deployment & Optimization: TensorRT, ONNX, OpenVINO, CUDA
Infrastructure: Linux, Docker, [GStreamer / V4L2], [AWS/GCP]
Hardware: NVIDIA Jetson, Edge TPUs, RGB/Depth Cameras, LiDAR

The Day-to-Day
Build the Pipeline: Architect and maintain end-to-end computer vision workflows, from camera sensor acquisition to model inference and post-processing.
Squeeze Out Performance: Profile code and optimize deep learning models (quantization, pruning) to hit strict real-time latency and FPS targets on constrained hardware.
Integrate Software & Hardware: Seamlessly connect vision algorithms with external sensors, edge compute boards, and broader system architecture.
Write Production Code: Deliver clean, thread-protected,



and highly efficient C++ and Python code.
Monitor & Iterate: Build automated CI/CD pipelines to test vision models, track data drift in the wild, and push over-the-air (OTA) updates.
Collaborate: Work hand-in-hand with Data Scientists to inform model architecture decisions based on actual hardware limits.

What You Bring
3+ years of skilled software engineering experience with a heavy focus on computer vision and ML deployment.
Deep expertise in writing production-ready C++ and Python.
Proven hands-on experience optimizing models using tools like TensorRT, ONNX, or CUDA.
A solid grasp of multi-threading, memory management, and concurrent programming in Linux environments.
A degree (BS, MS, or Ph.D.) in Computer Science, Robotics, Electrical Engineering, or a related field.

Bonus Points
You have successfully deployed ML models onto edge devices (NVIDIA Jetson, Coral, Raspberry Pi).
You have experience with 3D computer vision, point clouds, or SLAM.
You know your way around camera hardware, ISP tuning, and video streaming protocols (GStreamer).
You have background experience in [insert your specific industry: e.g., autonomous vehicles, ag-tech, medical imaging].

📌 Computer Vision Engineer Bengaluru
🏢 ETEL
📍 Bengaluru