Computer Vision Engineer

We are seeking a Computer Vision Engineer with 3 to 4 years of experience to design, train, optimize, and deploy computer vision models into production environments. This role involves working extensively with image and video understanding, deep learning techniques, and real-time inference systems. The candidate will manage the entire pipeline, from dataset preparation and model training to deployment and ongoing monitoring.

Key Responsibilities

- Build and train models for various computer vision tasks including image classification, object detection, segmentation, object tracking, and OCR/visual understanding.
- Fine-tune pre-trained vision models to improve performance.
- Conduct error analysis and iterate on models based on data-driven insights.
- Prepare and preprocess image and video datasets, managing annotations, augmentations, class imbalance, and ensuring label quality.
- Design appropriate train/validation/test splits to ensure robust model evaluation.
- Track experiments and maintain version control for models.
- Deploy models as APIs, batch jobs, or real-time video pipelines, optimizing for latency, throughput, GPU usage, and cost efficiency.
- Utilize tools such as ONNX, TensorRT, or TorchScript to optimize inference.
- Monitor deployed models continuously and retrain them as necessary to maintain accuracy and performance.

Required Qualifications

- 3 to 4 years of professional experience in computer vision and deep learning.
- Strong proficiency in Python programming.
- Hands-on experience with PyTorch and/or TensorFlow frameworks.
- Familiarity with OpenCV and torchvision or similar computer vision libraries.
- Solid understanding of convolutional neural networks (CNNs), Vision Transformers, object detection, segmentation, and transfer learning techniques.
- Knowledge of model evaluation metrics including Precision, Recall, Intersection over Union (IoU), and mean Average Precision (mAP).
- Proven experience deploying models into production environments.
- Comfortable working with Docker and Linux environments.
- Experience with GPU inference and optimization using ONNX or TensorRT.
- Ability to write maintainable, production-quality code beyond experimental notebooks.

Preferred Qualifications

- Experience with real-time video analytics and processing RTSP/CCTV camera streams.
- Familiarity with tracking algorithms such as ByteTrack or DeepSORT.
- Experience working with NVIDIA GPUs or embedded devices like Jetson.
- Knowledge of MLOps tools such as MLflow, Weights & Biases, or DVC for experiment tracking and model management.

This position offers the opportunity to work on cutting-edge computer vision technologies and contribute to impactful real-world applications. Candidates who thrive in a fast-paced environment and are passionate about advancing AI-driven visual understanding will find this role rewarding.