Senior Machine Learning Engineer - Ai

Machine Learning Model Development: Develop, train, and optimize Machine Learning models using a variety of tools and frameworks.

Data Preparation: Collect, clean, and preprocess data to ensure its quality and suitability for Machine Learning applications.

Feature Engineering: Create and select relevant features that improve model performance and predictive accuracy.

Algorithm Selection: Choose appropriate Machine Learning algorithms and techniques based on problem requirements and datasets.

Model Evaluation: Design and implement rigorous evaluation methodologies to assess the performance and robustness of Machine Learning models.

Deployment: Deploy Machine Learning models into production environments, ensuring scalability and reliability.

Monitoring and Maintenance: Continuously monitor model performance, identify and address issues, and retrain models as needed.

Education: At least a Bachelor's degree in computer science, Machine Learning, artificial intelligence, or a related field is preferred.

Experience: A minimum of 5 of hands-on experience in Machine Learning model development and deployment.

Programming Skills: Proficiency in programming languages such as Python and experience with Machine Learning libraries (e.g., TensorFlow, PyTorch, etc).

Deep Learning: Strong expertise in deep learning frameworks and architectures is a plus.

Data Handling: Excellent skills in data manipulation, preprocessing, and feature engineering.

Model Deployment: Experience with deploying Machine Learning models in production using containerization and orchestration tools (e.g., Docker, Kubernetes).