Highlights
Build and deploy cutting-edge AI models; work on scalable solutions for industrial use cases.
Description
Job Summary
pThis role is focused on developing and deploying real-world computer vision systems, combining deep learning, image processing, and scalable software to power intelligent visual applications. As a Computer Vision Engineer (Software Developer), you will build and deploy models for tasks such as object detection, segmentation, and tracking using Python-based frameworks like OpenCV, PyTorch, and TensorFlow.
Responsibilities
- Develop and deploy computer vision models for tasks such as object detection, segmentation, and tracking.
- Work with image and video datasets, including preprocessing, annotation, and augmentation.
- Implement solutions using Python-based frameworks such as OpenCV, PyTorch, and TensorFlow.
- Optimize models for real-time inference and performance.
- Integrate vision models into production systems and APIs.
- Collaborate with cross-functional teams including backend, hardware, and AI teams.
- Debug, test, and continuously improve model accuracy and robustness.
Required Skills
- Python
- OpenCV
- PyTorch
- TensorFlow
- Docker
Required Skills Explained
- Deep understanding of computer vision fundamentals, including image processing techniques and deep learning concepts such as CNNs and YOLO.
- Hands-on experience with Python libraries like OpenCV and NumPy for implementing solutions in computer vision tasks.
- Experience with deep learning frameworks such as PyTorch or TensorFlow for training and deploying models.
- Knowledge of model optimization techniques to ensure real-time inference and performance.
- Familiarity with working on large datasets, including preprocessing, annotation, and augmentation.
- Understanding of Linux environments and scripting in Python.
- Ability to work on edge deployments using GPU acceleration or NVIDIA DeepStream SDK (preferred).
- Experience collaborating with cross-functional teams for system integration and continuous improvement.
Who is this for
pIdeal candidates are driven, detail-oriented individuals with experience in software development and a strong understanding of computer vision fundamentals. A background in deep learning concepts and image processing techniques is essential.
Why This Job is a Good Opportunity
ulliPotential to work on cutting-edge AI applications that have real-world industrial use cases.liOpportunity to build scalable solutions for object detection, tracking, and automation projects.liA chance to stay at the forefront of AI advancements through continuous learning and collaboration with industry experts.liCompetitive salary and benefits package in a growing tech sector.liFlexible work environment that values creativity and innovation.
Interview Preparation Tips
- Review computer vision models, including CNNs and YOLO, to refresh your knowledge on the latest advancements.
- Practice coding exercises with Python libraries like OpenCV and NumPy to demonstrate your practical skills.
- Familiarize yourself with deep learning frameworks such as PyTorch or TensorFlow by building simple projects.
- Prepare examples of how you have optimized models for real-time inference in previous roles.
- Discuss real-world case studies where you worked on large datasets, including annotation workflows.
Career Growth in This Role
pThe role offers significant career growth opportunities as it involves working on scalable solutions and cutting-edge technology. As a Computer Vision Engineer, you can advance into senior positions such as Lead Engineer or Technical Manager by demonstrating leadership and technical expertise. The field is rapidly evolving, providing ample chances to learn new technologies and apply them in innovative ways. Collaboration with cross-functional teams also opens doors for growth in related areas like backend development, hardware engineering, and AI.
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Skills
Frequently Asked Questions
What is the ideal candidate background for this role?The ideal candidate should have a strong background in software development with experience in computer vision fundamentals, image processing techniques, and deep learning concepts.
Is experience with NVIDIA DeepStream SDK required?Experience with NVIDIA DeepStream SDK is preferred but not mandatory for this role.
What kind of projects can I expect to work on in this position?You will work on developing and deploying computer vision models for tasks such as object detection, segmentation, and tracking, along with integrating these models into production systems.
