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Data Science Solutions Architect
hace 7 días
About the Team:
We are looking for a highly skilled AI/ML Lead to join our team. The ideal candidate will have a robust background in machine learning, with a particular focus on AWS SageMaker, AWS Bedrock, and generative AI solutions.
About the Position:
- Design, develop, and deploy machine learning models and algorithms to solve complex business problems.
- Oversee the end-to-end machine learning lifecycle, including data preprocessing, model training, evaluation, and deployment.
- Collaborate with cross-functional teams to integrate ML models into production environments and applications.
- Develop and implement generative AI solutions to enhance business processes and customer experiences.
- Implement MLOps practices, including model monitoring, and automation of the training and deployment pipeline.
Requirements:
- Minimum of 7 years of hands-on experience in machine learning and data science roles, with significant experience in leading and managing ML projects.
- Proven track record of successfully delivering end-to-end machine learning solutions from concept to production deployment.
- Extensive expertise in AWS services such as SageMaker, AWS Bedrock, and other AI/ML tools.
- Strong proficiency in Python and familiarity with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn.
- Experience with MLOps practices, including model monitoring, deployment automation, and CI/CD pipelines.
- Demonstrated ability to design and implement scalable and efficient machine learning architectures in cloud environments.
- Deep understanding of data engineering, feature engineering, and data preprocessing techniques.
- Experience with AutoML, hyperparameter tuning, and model optimization techniques.
- Leadership skills with the ability to lead and mentor a team of data scientists and machine learning engineers effectively.
