Job Description: Machine Learning Expert for Image Segmentation using Mask R-CNN and Deployment via Docker and Azure
We are seeking a talented and experienced Machine Learning Expert to join our team and assist us in implementing advanced image segmentation models using Mask R-CNN. As a skilled professional, you will play a crucial role in developing, training, evaluating, and deploying machine learning models for our exciting projects.
Responsibilities:
Mask R-CNN Implementation: Utilize your expertise in machine learning and specifically in the Mask R-CNN framework to develop efficient and accurate image segmentation models.
Data Preprocessing: Process and prepare datasets for training, ensuring high-quality input data for optimal model performance.
Model Training and Evaluation: Design and execute training routines, fine-tuning hyperparameters for the Mask R-CNN model, and assessing its performance using various evaluation metrics.
Troubleshooting and Optimization: Identify and address issues related to model performance, fine-tuning, and convergence to enhance model accuracy and efficiency.
Deployment and Containerization: Implement model deployment using Docker containers, ensuring seamless integration and scalability.
Cloud Deployment with Azure: Utilize Azure cloud services to deploy machine learning models effectively, enabling real-time processing and accessibility.
Collaboration: Work closely with our development team, providing guidance and support on integrating machine learning models into existing applications or systems.
Requirements:
Proven Experience: Demonstrated experience in implementing machine learning models, particularly in the field of image segmentation. Experience with Mask R-CNN is highly preferred.
Data Science and AI: Solid understanding of data science principles and hands-on experience with popular machine learning libraries and frameworks.
Training and Evaluation: Proficiency in training machine learning models, fine-tuning hyperparameters, and evaluating model performance using various metrics.
Docker and Containerization: Experience with Docker and containerization, enabling smooth and efficient deployment of machine learning models.
Cloud Services: Familiarity with cloud platforms, particularly Microsoft Azure, for deploying and managing machine learning applications.
Problem-Solving: Strong analytical and problem-solving skills, with the ability to address complex challenges related to model development and deployment.
Additional Qualifications:
Reliability: We are looking for a candidate who demonstrates a high level of reliability and accountability in their work. You should have a track record of consistently delivering high-quality results on time and meeting project deadlines.
Timelines Adherence: Capability to stick to timelines and manage project schedules efficiently is essential. You should possess strong time management skills to ensure timely completion of tasks and milestones.
Communication: Effective communication skills to collaborate with team members, explain technical concepts, and present findings.
We aim to establish a long-term professional relationship. While the immediate focus is on smaller projects, we intend to expand our collaboration on more extensive and challenging initiatives in the future. Ideally, you should be open to such long-term engagement and show enthusiasm for potential future endeavors.
If you are a passionate Machine Learning Expert with a proven track record in image segmentation and have hands-on experience with Mask R-CNN, we would love to hear from you. Join us in this exciting opportunity to contribute to cutting-edge projects and make a significant impact using your machine learning expertise.
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