Computer Vision Engineer Developer

Experience: 520 Years

Location: PAN India

Employment Type: Full-Time

Job Type: AI / Machine Learning / Computer Vision

Role Overview

We are looking for experienced Computer Vision Engineers / Developers to design, develop, optimize, and deploy AI-driven computer vision solutions for real-world applications.

The role involves working on object detection, object tracking, image/video recognition, classification, segmentation, counting, OCR, visual inspection, and video analytics. The ideal candidate should have strong hands-on experience in deep learning, computer vision algorithms, model development, dataset preparation, and production deployment.

Candidates across 5–20 years of experience are welcome, with responsibilities ranging from hands-on development to technical leadership and architecture.

Key Responsibilities

- Design and develop computer vision and deep learning pipelines for image and video-based applications.
- Develop solutions for object detection, classification, recognition, tracking, segmentation, and counting.
- Work with images, videos, CCTV streams, edge devices, and real-time vision systems.
- Build, train, fine-tune, and evaluate deep learning models.
- Work with frameworks such as PyTorch, TensorFlow, OpenCV, ONNX, and YOLO.
- Prepare, clean, annotate, augment, and validate large-scale image/video datasets.
- Implement data preprocessing, feature extraction, model inference, and post-processing pipelines.
- Experiment with CNNs, Vision Transformers (ViT), Transformers, foundation models, and multimodal models.
- Optimize models for accuracy, latency, memory consumption, and real-time inference.
- Convert and optimize models using ONNX, TensorRT, TorchScript, or similar technologies.
- Develop solutions for real-world challenges such as occlusion, lighting variation, camera angle changes, motion blur, and varying object sizes.
- Evaluate models using appropriate metrics such as Precision, Recall, F1-score, mAP, IoU, ROC-AUC, and tracking metrics.
- Integrate computer vision models with backend services, APIs, and enterprise applications.
- Support deployment of AI models in cloud, on-premises, and edge environments.
- Work closely with Data Scientists, ML Engineers, Software Engineers, and Product teams.
- Troubleshoot model performance and production issues.
- Maintain technical documentation,



experiment results, model versions, and deployment artifacts.

Required Technical Skills

Programming

- Strong proficiency in Python.
- Good understanding of C++ is an advantage.
- Experience with NumPy, Pandas, SciPy and related libraries.

Computer Vision
- OpenCV
- Image processing
- Video processing
- Object detection
- Object tracking
- Image classification
- Image segmentation
- OCR
- Pose estimation
- Feature extraction
- Visual similarity / image matching

Deep Learning

Strong knowledge of

- CNN architectures
- ResNet / EfficientNet / MobileNet
- YOLO family
- Faster R-CNN / Mask R-CNN
- Vision Transformers
- Transformers
- Siamese / metric-learning approaches
- Segmentation models
- Transfer learning
- Model fine-tuning

AI / Foundation Models Exposure to one or more of:
- Vision Foundation Models
- CLIP
- SAM / Segment Anything
- Vision-Language Models
- Multimodal AI
- Generative AI for vision
- Synthetic data generation
- LLM + Vision integration

ML Engineering / Deployment
- Model serving and inference pipelines
- REST APIs / FastAPI
- Docker / Kubernetes
- CI/CD
- MLflow or equivalent model lifecycle tools
- ONNX / TensorRT
- GPU-based inference
- AWS / Azure / GCP
- Edge AI deployment

Dataset & Model Development
- Experience with image/video data collection and preprocessing.
- Understanding of annotation tools and dataset management.
- Experience handling class imbalance, noisy labels, and dataset bias.
- Data augmentation and synthetic data generation.
- Train/validation/test dataset strategy.
- Model benchmarking and performance optimization.
- Experience with production-scale datasets is preferred.

Senior-Level Expectations – 10–15 Years
- Own end-to-end computer vision solutions from problem definition through production deployment.
- Design scalable CV/AI architectures.
- Lead model selection, experimentation, optimization, and deployment.
- Mentor junior and mid-level engineers.




- Define technical standards and development best practices.
- Work with stakeholders to translate business problems into computer vision solutions.
- Drive POCs and transition successful solutions into production.
- Improve model accuracy, latency, scalability, and reliability.

Lead / Architect Expectations – 15–20 Years
- Define the overall Computer Vision / AI technical architecture.
- Lead large-scale computer vision and AI initiatives.
- Design reusable CV platforms, frameworks, and production pipelines.
- Evaluate emerging technologies, foundation models, and AI architectures.
- Drive technical strategy for vision AI, multimodal AI, and intelligent video analytics.
- Lead architecture reviews, technical decisions, and engineering standards.
- Mentor senior engineers and technical leads.
- Collaborate with business, product, engineering, and data science leadership.
- Establish best practices around MLOps, model governance, scalability, security, and responsible AI.

Positive to Have
- Experience with NVIDIA GPUs, CUDA, TensorRT.
- Experience with real-time video analytics.
- Experience with edge AI / embedded vision.
- Experience with autonomous systems, robotics, retail, manufacturing, surveillance, healthcare, or industrial vision.
- Knowledge of 3D computer vision / LiDAR / depth cameras.
- Experience with synthetic data platforms.
- Experience with multimodal / Vision-Language Models.
- Publications, patents, or contributions to open-source AI/CV projects.

Education
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Electrical Engineering, Computer Engineering, or a related field.
- Strong practical experience may be considered in lieu of an advanced degree.

Core Competencies Python | OpenCV | PyTorch | TensorFlow | YOLO | Object Detection | Object Tracking | Image Classification | Image Segmentation | Deep Learning | Computer Vision | Transformers | Vision Transformers | OCR | Foundation Models | Synthetic Data | Vision-Language Models | ONNX | TensorRT | MLOps | Cloud | Edge AI | GPU

Experience Range

- 5–8 Years: Senior Computer Vision Engineer / Developer
- 8–12 Years: Lead Computer Vision Engineer
- 12–15 Years: Principal / Senior Lead – Computer Vision
- 15–20 Years: Computer Vision Architect / AI Architect / Technical Lead

📌 Hiring For computer vision engineer (Bengaluru)
🏢 Glauben Technologies
📍 Bengaluru