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Key Responsibilities
Your primary responsibilities will include:
- Designing, building, and optimizing data workflows for Machine Learning and GenAI solutions in cloud environments.
- Developing and deploying Machine Learning and Generative AI (GenAI) models using AWS SageMaker.
- Creating and managing data and model pipelines to improve the efficiency of AI and machine learning systems.
- Preparing and structuring data for advanced AI and GenAI solutions.
- Ensuring seamless integration of data and AI solutions within cloud architectures, including data security and governance aspects.
- Documenting and rigorously testing models and workflows to meet accuracy and performance requirements.
- Monitoring and enhancing the performance of Machine Learning models and services in production.
Requirements
To be successful in this role, you will need to have:
- Proven experience as a Machine Learning Engineer or in Data Science roles, with strong skills in data pipelines and Machine Learning model development.
- Experience working in cloud environments (AWS) for at least 2 years.
- Solid proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or similar.
- Advanced English level.
- Experience using SageMaker and other AWS data services: S3, AWS Glue, Athena.
- Experience with Generative AI models and deploying them in production.
- Proficiency in DevOps tools (Git, pipelines) and infrastructure as code (Terraform, CloudFormation).
- Ability to work in Agile teams under Scrum methodology.
