Senior Computer Vision Engineer

Coimbatore, Tamil Nadu
Permanent
Full-time

12 hours ago
Apply easily

Location: Coimbatore
Work Mode: Onsite
Experience: 3 5 Years

1. Role OverviewWe are looking for a Senior Computer Vision Engineer with hands-on experience in designing, developing, and deploying computer vision solutions using deep learning. The role involves working on image and video processing pipelines, real-time systems, and scalable deployment environments. The candidate will collaborate with cross-functional teams to build and integrate production-grade vision systems. 2. Key Responsibilities

Design and develop computer vision models for image and video-based applications
Implement deep learning models for object detection, segmentation, tracking, and feature extraction
Build and optimize end-to-end CV pipelines for real-time and batch processing
Deploy CV models in on-premises environments and ensure system reliability
Work with high-volume video streams and implement real-time processing solutions
Integrate CV systems with existing infrastructure, databases, and enterprise systems
Perform model optimization including compression and quantization
Develop scalable solutions using containerization and orchestration tools
Implement load balancing and scaling strategies across distributed systems
Collaborate with MLOps teams for model versioning, experiment tracking, and CI/CD pipelines
Ensure adherence to security best practices for model and data protection
Support debugging, performance tuning, and production monitoring

3. Required Qualifications

Bachelor's or Master's degree in Computer Science, Electronics, Electrical Engineering, or related field
3 5 years of experience in computer vision and deep learning-based solutions
Strong foundation in machine learning, deep learning, and image processing concepts
Experience in deploying production-grade CV systems

4. Technical SkillsProgramming & Frameworks:

Python, C++
PyTorch, TensorFlow, Keras

Computer Vision & Deep Learning:

CNNs, RNNs, GANs
Object Detection, Image Segmentation, Tracking
Feature Extraction and Image Processing

Libraries & Tools:

OpenCV, scikit-image, PIL/Pillow
Data Annotation Tools: LabelImg, CVAT, RectLabel

Systems & Deployment:

On-premises deployment of CV models
Real-time streaming (Kafka or similar)
Distributed systems and scaling

DevOps & MLOps:

Git, GitHub, GitLab
Docker, Kubernetes
Model versioning, experiment tracking, CI/CD

Optimization Techniques:

Model compression
Quantization

Infrastructure & Integration:

Integration with enterprise systems and databases
Load balancing and multi-machine scaling

Security:

Secure deployment practices for CV models and data

5. Good to Have (Optional)

Experience with hybrid cloud platforms (AWS, Azure, Google Cloud)
Exposure to edge devices (NVIDIA Jetson, Intel NUC, embedded systems)
Experience in high-throughput streaming systems (Kafka)
Knowledge of distributed computing and large-scale CV systems

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