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AI Data Engineer
5 months ago
Primary Purpose :
Building and maintaining the company's data infrastructure on the AWS cloud platform, with a specific focus on supporting AI model training, development, and deployment. This includes designing, developing, and implementing data pipelines, ensuring the secure and efficient flow of data for our AI models.
Responsibilities :
Data for AI :
- Design and implement data pipelines specifically tailored for AI training and model development.
- Partner with AI data scientists and engineers to understand their data needs and ensure efficient data access.
- Implement data pre-processing and feature engineering techniques for optimal model performance.
- Design, develop, and maintain data infrastructure on the AWS cloud platform, leveraging services like S3,Redshift, Glue, Lambda, and Kinesis.
- Build and maintain data lakes and warehouses optimized for AI workloads.
- Implement automated data transformations, cleansing, and validation processes to ensure data quality.
- Write code using Python, SQL, and other relevant programming languages, with a focus on libraries and frameworks commonly used in AI (e.g., TensorFlow, PyTorch).
- Automation and monitoring:
- Automate data pipelines using CI/CD tools and related techniques.
- Monitor and troubleshoot data pipelines for performance, reliability, and data quality issues.
3 to 8 years of experience as a Data Engineer or similar role, with a demonstrated experience in supporting data pipelines for AI applications and their data requirements.
Experience :
- Proven experience with AWS services including S3, Redshift, Glue, Lambda, and Kinesis.
- Strong experience with Python and SQL.
- Strong understanding of AI libraries and frameworks.
- Experience with data warehousing and data modeling concepts.
- Excellent problem-solving and analytical skills.
- Ability to work independently and as part of a collaborative team.
- Strong communication and collaboration skills.
(ref:hirist.tech)