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Image Segmentation Specialist
4 months ago
Job Summary
The Image Segmentation AI/ML Specialist will play a crucial role in developing and optimizing advanced image segmentation algorithms. This individual will work closely with our team to design, implement, and deploy state-of-the-art segmentation models that can accurately identify and delineate objects within images. The ideal candidate will have a strong background in computer vision, deep learning, and image processing, and large dataset analytics.
Responsibilities
Algorithm Development:
Develop, implement, and optimize image segmentation algorithms using machine learning and deep learning techniques.
Research and integrate the latest advancements in AI and computer vision into existing workflows.
Model Training & Evaluation:
Create and maintain datasets for training and evaluating segmentation models.
Train, validate, and fine-tune models to achieve high accuracy and performance.
Optimize large data sets for detection and tracking accuracy.
Collaboration & Communication:
Work closely with cross-functional teams, including data scientists, software engineers, and product managers, to integrate segmentation solutions into products.
Present findings and progress to stakeholders, ensuring clarity and understanding of technical details.
Performance Optimization:
Identify and address performance bottlenecks in algorithms and models.
Ensure solutions are scalable and efficient for real-time applications.
Documentation & Reporting:
Document methodologies, experiments, and code for reproducibility and knowledge sharing.
Prepare technical reports and presentations to communicate results and insights.
Requirements
- Advanced degree in Computer Science, Electrical Engineering, or a related field with a focus on computer vision and machine learning.
- Minimum of 4 years of experience in developing and deploying image segmentation algorithms.
- Proven track record of working on successful AI/ML projects, preferably in a commercial setting.
- Strong proficiency in programming languages such as C, and Python and libraries/frameworks such as TensorFlow, PyTorch, OpenCV, and scikit-learn.
- Deep understanding of convolutional neural networks (CNNs) and other relevant deep learning architectures.
- Experience with image processing techniques and tools. (Labellerr, Labelbox, V7 Labs, Encord, CVAT, Dataturks, Roboflow)
- Strong analytical and problem-solving skills.
- Excellent communication and teamwork abilities.
- Demonstrated ability to stay current with the latest research and advancements in AI and computer vision.
- Ability to work in an ambiguous, dynamic environment with highly complex technologies.
