Computer Vision Engineer
1 day ago
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
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