Job Description: We are seeking a skilled SageMaker Expert to join our team. The ideal candidate will have extensive experience in utilizing Amazon SageMaker for data processing and modeling.
Candidate will be responsible for developing and deploying machine learning within the SageMaker environment.
Key Responsibilities:
- Pull and process data from Amazon S3 for analysis and modeling.
- Utilize Amazon SageMaker to build, train, and deploy machine learning models.
- Develop and maintain interactive web applications that allow you to create and share documents containing live code, equations, visualizations, and narrative text for data exploration, preprocessing, and modeling.
- Collaborate with data engineers and other stakeholders to understand data requirements and ensure data quality.
- Implement best practices for version control, reproducibility, and documentation of modeling processes.
- Monitor and optimize model performance, ensuring they meet business objectives.
- Stay updated on the latest trends and technologies in machine learning and cloud computing.
Qualifications:
- Bachelor's degree in Computer Science, Data Science, Engineering, or a related field.
- Proven experience with Amazon SageMaker and AWS services, particularly S3.
- Strong proficiency in Python, including libraries such as Pandas, NumPy, and Scikit-learn.
- Experience with Jupyter Notebooks for data analysis and modeling.
- Familiarity with machine learning algorithms and frameworks (e.g.,TensorFlow, PyTorch).
- Excellent problem-solving skills and the ability to work independently and in a team environment.
- Strong communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Experience with data visualization tools (e.g., Matplotlib, Seaborn).
- Knowledge of containerization technologies (e.g., Docker) is a plus.
- Familiarity with CI/CD practices for machine learning.