• Strong computer science fundamentals such as algorithms, data structures, multithreading, object-oriented development, distributed applications, client-server architecture.
• Design and implement Machine learning models and data ingestion pipelines.
• Develop and support a platform that enables data scientists to rapidly develop, train, and experiment with machine learning models.
• Expand and optimize data pipelines, data flow, and collection for cross-functional teams.
• Create and maintain optimal data pipeline architecture by assembling large, complex data sets to meet functional and non-functional business requirements.
• Identify and implement internal process improvements including automating manual processes, optimizing data delivery, and redesigning infrastructure for greater scalability.
• Support the building of machine learning, data platforms, and infrastructure required for optimal data extraction, transformations, and loading of data from a wide variety of data sources.
• Partner with data scientists to understand, implement, train, and design machine learning models.
• Collaborate with the infrastructure team to improve the architecture, scalability, stability, and performance of the Client platform.
• Develop processes, model monitoring, and governance framework for successful Client model operationalization.
• Work with architecture, data, and design teams to assist with data-related technical issues and support data infrastructure needs.
• Implement Machine Learning (Client) and Big Data platforms in Hybrid and multi-cloud environments specifically in the AWS SageMaker environment
• Experience in a container, streaming, and messaging technologies is a plus

Skills / Qualifications:

·         Bachelor's degree in computer science, computer engineering or any other relevant field of engineering-  Masters' degree preferred

·         At least Three years experience as a machine learning engineer.

·         Advanced proficiency with Python framework, Java, and Scala

·         Extensive knowledge of Client frameworks, libraries, data structures, data modeling, and software architecture.

·         Good understanding of mathematics, statistics, and algorithms.

·         Excellent analytical and problem-solving abilities.

·         Great communication and collaboration skills