Computer Vision Engineer

Description :

Job Title : Computer Vision Engineer (5 - 8 Years Experience)

Location : Bangalore

Key Responsibilities :

Computer Vision Development :

- Design and develop advanced computer vision algorithms and models for image and video analysis.

- Implement solutions for object detection, semantic segmentation, instance segmentation, and multi-object tracking.

- Develop and train deep learning models using CNN-based architectures for vision tasks.

- Implement state-of-the-art detection and segmentation frameworks such as YOLO, Faster R-CNN, SSD, and Mask R-CNN.

- Optimize models for accuracy, efficiency, and real-time performance.

- Fine-tune pretrained models and perform hyperparameter tuning to improve results.

Image Processing & Vision Techniques :

- Apply classical computer vision techniques such as filtering, edge detection, feature matching, and morphological operations.

- Implement advanced image processing methods using OpenCV and Scikit-image.

- Work on image enhancement, denoising, color correction, and feature engineering.

Video Analytics & Tracking :

- Develop algorithms for video analytics and real-time object tracking.

- Implement multi-object tracking systems using modern tracking algorithms.

- Build systems capable of handling live camera streams and video datasets.

Generative AI for Images :

- Work with generative AI models for image synthesis, image-to-image translation, super-resolution, and inpainting.

- Implement data augmentation strategies using generative models to improve dataset diversity.

- Explore diffusion models, GANs, and other generative techniques for image generation and enhancement.

3D Vision & Spatial Understanding :

- Develop solutions related to 3D vision and spatial perception.

Implement techniques such as :

1. Depth estimation

2. 3D reconstruction

3. Multi-view geometry

4. Point cloud processing

- Work with stereo vision systems and depth sensors for 3D scene understanding.

Edge AI Deployment :

Deploy optimized computer vision models on edge devices and embedded platforms such as :

1. NVIDIA Jetson

2. Edge GPUs

3. Embedded AI systems

- Optimize models for low-latency inference and real-time performance.

Model Optimization & Acceleration :

Apply model optimization techniques including :

1. Quantization

2. Pruning

3. Knowledge distillation

- Convert and deploy models using frameworks such as ONNX, TensorRT, and OpenVINO.

- Improve inference performance and reduce memory footprint for edge deployment.

End-to-End AI System Development :

- Build end-to-end pipelines from data preprocessing to model deployment.

- Integrate AI models into production systems and APIs.

- Ensure solutions are scalable, robust, and production-ready.

Collaboration & System Integration :

- Collaborate with software engineers, DevOps teams, and product managers.

- Integrate AI models into existing applications, microservices, and cloud infrastructure.

- Participate in code reviews and maintain high standards of software quality.

Required Skills :

Experience :

- 4 to 8 years of professional experience in Computer Vision and Deep Learning.

Programming Skills :

- Strong proficiency in Python.

Experience with scientific computing libraries such as :

1. NumPy

2. OpenCV

3. Scikit-image

Computer Vision Expertise :

Hands-on experience in :

1. Image processing

2. Video processing

3. Feature extraction techniques

4. Object detection

5. Multi-object tracking

6. Image segmentation (semantic and instance)

Deep Learning Frameworks :

- Strong experience with TensorFlow or PyTorch.

- Understanding of CNN architectures and vision models.

Detection & Segmentation Frameworks :

Experience with modern frameworks including :

1. YOLO

2. Faster R-CNN

3. SSD

4. Mask R-CNN