Computer Vision Engineer

Responsibilities:

• Design, develop, and implement computer vision algorithms and models for image and video analysis, object detection, recognition, and tracking.
• Collaborate with cross-functional teams to understand business requirements and translate them into technical specifications for computer vision solutions.
• Conduct research and stay updated with the latest advancements in computer vision and deep learning to identify opportunities for innovation.
• Work with large datasets and use data preprocessing techniques to ensure high-quality training and testing of computer vision models.
• Optimize and fine-tune computer vision models for efficiency, accuracy, and real-time performance.
• Perform code reviews and maintain best practices for software development in computer vision.
• Collaborate with hardware and software teams to integrate computer vision solutions into products and services.
• Participate in the design and development of data annotation pipelines to support computer vision tasks.
• Conduct experiments and analyze results to evaluate the effectiveness of computer vision algorithms and models.
• Assist in the deployment and testing of computer vision models in real-world scenarios.
• Troubleshoot and debug issues related to computer vision algorithms and implementations.
• Participate in brainstorming sessions and contribute to the ideation and innovation process.
• Work in a collaborative and fast-paced startup environment, contributing to the growth and success of the company.

Requirements:

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or a related field.
• Solid understanding of computer vision fundamentals and deep learning techniques.
• Proficiency in programming languages such as Python, C++, or Java.
• Experience with popular computer vision libraries and frameworks (e.g., OpenCV, TensorFlow,
• PyTorch,Keras).
• Demonstrated experience in implementing computer vision models for various applications such as
• Facial detection, automatic number plate recognition, NLP.
• Familiarity with data preprocessing, data augmentation and data annotation processes for computer vision tasks.
• Hands on experience in identifying outlier detection and testing it with different methods
• Hands on experience in identifying data imbalance, data compatibility, data privacy, data normalization, Data encoding issues
• Hands on experience in Data reduction techniques, feature selection, wrapper methods, feature stabilization, labeling accuracy
• Hands on experience in Model Selection, model evaluation, Model Training, Model validation and testing different methods and scenarios
• Hands on experience in deploying ML/DL projects using Conda, docker, Kuberntesses
• Ability to test AI/ML models in different field conditions
• Ability to collect data from field, synthetic data etc basis project requirement
• Ability to test AI/ML model with performance optimization and Latency test scenario
• Ability handle different error handling scenarios on production enviournment such as out of memory, resource exhaustion, network failure, data integrity testing
• Excellent communication and collaboration skills to work effectively with cross-functional teams.
• Prior experience in a startup environment or personal projects in computer vision is a plus