Custom Software Engineer
Project Role Description : Develop custom software solutions to design, code, and enhance components across systems or applications. Use modern frameworks and agile practices to deliver scalable, high-performing solutions tailored to specific business needs.
Must have skills : Edge Computing
Good to have skills : NA
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an Edge Computing and Computer Vision Technical Lead, you will design and develop Edge AI and Computer Vision solutions involving cameras, sensors, edge compute platforms and Artificial Intelligence/Machine Learning (AI/ML) models. You will be expected to contribute hands-on to solution design, development, model deployment and optimization while guiding engineering teams through Proof of Concept (PoC), pilot and production deployments.
Roles & Responsibilities:
Design and develop end-to-end Edge AI and Computer Vision solutions.
Evaluate and integrate edge compute platforms such as NVIDIA Jetson, industrial Personal Computers (PCs), Graphics Processing Unit (GPU) and Neural Processing Unit (NPU) based devices.
Work with RGB (Red-Green-Blue), thermal/infrared, low-light, stereo, depth and Time-of-Flight (ToF) camera technologies.
Integrate cameras, sensors and actuators such as LiDAR (Light Detection and Ranging), radar, ultrasonic sensors, Inertial Measurement Units (IMUs), relays, motors and Programmable Logic Controllers (PLCs).
Develop Computer Vision applications for object detection, classification, segmentation, tracking, Optical Character Recognition (OCR), pose estimation and anomaly detection.
Work with model architectures such as YOLO, SSD, Faster R-CNN, Mask R-CNN, DETR, U-Net and Vision Transformers (ViTs).
Optimize models for edge deployment using quantization, pruning, FP16/INT8 inference and hardware acceleration.
Develop video and inference pipelines using OpenCV, GStreamer, NVIDIA TensorRT, NVIDIA DeepStream, Intel OpenVINO and ONNX Runtime.
Work with camera interfaces and protocols such as USB, MIPI-CSI (Mobile Industry Processor Interface – Camera Serial Interface), GigE Vision, RTSP (Real-Time Streaming Protocol) and ONVIF.
Support camera calibration, multi-camera synchronization, image preprocessing and sensor fusion.
Develop edge applications using Python, C/C++, Linux and Docker/container technologies.
Implement device monitoring, logging, Over-the-Air (OTA) software/model updates and remote troubleshooting capabilities.
Support edge-to-cloud integration using MQTT (Message Queuing Telemetry Transport), REST APIs and Internet of Things (IoT) platforms.
Participate in Proof of Concept, pilot and production deployments at customer locations.
Troubleshoot issues across cameras, edge hardware, operating systems, networks, AI models and applications.
Guide junior engineers and contribute to technical reviews and solution design discussions.
Professional & Technical Skills:
Must To Have Skills: Strong hands-on experience in Edge Computing, Computer Vision and Machine Learning.
Good understanding of NVIDIA Jetson, industrial edge PCs and AI accelerator-based hardware.
Strong knowledge of camera technologies, image/video processing and camera integration.
Strong understanding of Computer Vision algorithms and model architectures.
Experience with PyTorch, TensorFlow and Open Neural Network Exchange (ONNX).
Strong programming experience in Python and preferably C/C++.
Experience optimizing models for latency, Frames Per Second (FPS), memory, power and compute constraints.
Experience with Linux, Docker and embedded/edge software environments.
Understanding of networking, IoT protocols and edge-to-cloud communication.
Experience handling real-world Computer Vision challenges such as low light, glare, occlusion, motion blur, vibration and changing environmental conditions.
Understanding of Machine Learning Operations (MLOps), model versioning and deployment lifecycle.
Strong debugging and problem-solving skills across hardware and software layers.
Additional Information:
The candidate should have minimum 8 years of overall software engineering experience with significant hands-on experience in Edge Computing and Computer Vision.
Candidate should have experience taking at least one Computer Vision solution from Proof of Concept through pilot or production deployment.
Experience with distributed deployments involving multiple cameras and edge devices is preferred.
Experience in industrial, manufacturing, transportation, automotive, retail, robotics or smart infrastructure domains will be an advantage.
This position is based at our Bengaluru office.
A 15 years full time education is required.
Bengaluru
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