Machine Learning Engineer
4 days ago
1. Design, develop, and deploy machine learning models for computer
2. Collaborate with cross-functional teams to understand project
requirements, gather data, and define model performance metrics.
3. Pre-process and augment image datasets to enhance model
performance and generalization.
4. Train, fine-tune, and optimize YOLO models for various object detection
and recognition tasks.
5. Evaluate and select appropriate machine learning models based on
project requirements, performance metrics, and computational constraints.
6. Implement and integrate machine learning models into production
systems, ensuring scalability and reliability.
7. Monitor and maintain deployed models, performing regular updates and
improvements as needed.
8. Stay up-to-date with the latest advancements in machine learning and
computer vision, and actively contribute to the development of new
techniques and approaches.
9. Document and present findings, methodologies, and results to both
technical and non-technical stakeholders.
**Requirements**:
1. Bachelor's or Master's degree in Computer Science, Artificial Intelligence,
or a related field.
2. Minimum of 4 years of professional experience in developing and
deploying machine learning models, with a strong emphasis on computer
3. Extensive knowledge of machine learning concepts, algorithms, and
frameworks, including but not limited to CNN, RNN, LSTM, and
Transformers.
4. Proven track record of selecting and implementing appropriate machine
learning models based on project requirements and performance metrics.
5. Proficiency in programming languages such as Python, C++, and Java,
along with experience in deep learning frameworks like TensorFlow,
PyTorch, or Keras.
6. In-depth understanding and hands-on experience with the YOLO object
detection framework, including training, fine-tuning, and deploying YOLO
7. Familiarity with computer vision techniques, including image
preprocessing, augmentation, segmentation, and object tracking.
8. Strong problem-solving skills and the ability to analyze and optimize
model performance.
9. Excellent communication and collaboration skills, with the ability to work
effectively in a team environment.
10. Experience with version control systems (e.g., Git) and collaborative
development tools (e.g., Jira, Confluence).
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