Sr. Computer Vision & Edge AI Engineer
Quick Summary
Job Title: Senior Computer Vision & Edge AI Engineer Experience:5+ Years Location:Pune (Work From Office)
Design, develop, and optimize computer vision models for: Object Detection Image & Instance Segmentation Multi-Object Tracking Human Pose Estimation Build and train deep learning models using frameworks such as PyTorch or TensorFlow.
5+ years of hands-on experience in Computer Vision and Deep Learning. Strong expertise in: Object detection architectures (e.g., YOLO, Faster R-CNN, SSD) Segmentation models (e.g., U-Net, Mask R-CNN) Tracking algorithms (e.g., DeepSORT, ByteTrack)…
- Design, develop, and optimize computer vision models for:
- Object Detection
- Image & Instance Segmentation
- Multi-Object Tracking
- Human Pose Estimation
- Build and train deep learning models using frameworks such as PyTorch or TensorFlow.
- Convert and optimize models for edge deployment using:
- TensorRT
- OpenVINO
- NVIDIA TAO Toolkit
- Perform model quantization, pruning, benchmarking, and latency optimization.
- Deploy models on edge hardware platforms (NVIDIA Jetson, Intel-based edge devices, NVIDIA IGX Orin, etc.).
- Write clean, scalable, and production-ready Python code.
- Collaborate with cross-functional teams including ML engineers, software developers, and hardware teams.
- Conduct performance evaluation, debugging, and continuous improvement of deployed systems.
- Stay updated with the latest research and advancements in computer vision and edge AI.
- 5+ years of hands-on experience in Computer Vision and Deep Learning.
- Strong expertise in:
- Object detection architectures (e.g., YOLO, Faster R-CNN, SSD)
- Segmentation models (e.g., U-Net, Mask R-CNN)
- Tracking algorithms (e.g., DeepSORT, ByteTrack)
- Pose estimation frameworks (e.g., OpenPose, HRNet)
- Proven experience deploying optimized models using:
- TensorRT
- OpenVINO
- NVIDIA TAO Toolkit
- Strong Python programming skills.
- Experience with model optimization techniques (INT8 quantization, FP16, pruning).
- Familiarity with ONNX and model conversion pipelines.
- Strong understanding of GPU acceleration and edge hardware constraints.
Location & Eligibility
Listing Details
- First seen
- May 13, 2026
- Last seen
- May 13, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 51%
- Scored at
- May 13, 2026
Signal breakdown
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