About the Job
We are looking for a Machine Learning Engineer with a strong background in computer vision, machine learning, and software development. In this role, you will develop and optimize models for efficient deployment on constrained devices, working on projects that range from image segmentation to scalable model deployment.
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Key Responsibilities
- Algorithm Development: Create and optimize computer vision algorithms for tasks like object detection and tracking using TensorFlow and PyTorch.
- Data Handling: Preprocess, augment, and annotate data using tools such as OpenCV and LabelImg.
- Model Training and Evaluation: Train and fine-tune models, evaluating performance with metrics like Intersection over Union (IoU) and Dice Coefficient.
- Model Optimization: Implement quantization techniques to reduce model size and enhance speed, using tools like TensorFlow Lite and NVIDIA TensorRT.
- Deployment and Integration: Deploy models using TensorFlow Serving, Docker, and Kubernetes, ensuring seamless integration across platforms.
- Research and Development: Stay updated with the latest advancements and conduct experiments to improve models.
- Collaboration and Documentation: Work with cross-functional teams and document processes for knowledge sharing.
Required Qualifications
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field.
- 5+ years in computer vision and machine learning, with experience in TensorFlow, PyTorch, and OpenCV.
- Proficiency in Python and C++, with a strong understanding of deep learning architectures and experience with model deployment and optimization tools.
The selected candidates will be invited to an interview for further discussion.
