ML Data Pipelines Architect for AI Solutions

Flexjet; United States; On-site; USD 120,000 - 160,000; Full time

Job summary

Flexjet is seeking a detail oriented AI Data Engineer to build and maintain data infrastructure that powers machine learning and AI systems. You will work closely with data scientists, ML engineers and software teams to ensure high quality, reliable and scalable data pipelines for AI applications.

The role involves designing and maintaining data pipelines for AI/ML workflows, collating clean data, and developing datasets for model training, validation and inference, while ensuring data quality

Qualifications

• Bachelor's degree or equivalent experience in CS/Data Engineering/IS or related field.
• Strong programming skills in Python and SQL.
• Understanding of ETL/ELT, data modeling and data warehousing.
• Familiarity with ML workflows and data requirements.
• Experience with data processing tools e.g. Pandas, Spark.
• Knowledge of relational and non-relational databases.
• Basic understanding of cloud platforms AWS/Azure or Google Cloud.

Responsibilities

• Design, build and maintain data pipelines for AI/ML workflows.
• Collect, clean and preprocess structured and unstructured data.
• Develop datasets for model training, validation and inference.
• Collaborate with ML engineers and data scientists to support model development.
• Ensure data quality, integrity and availability across systems.
• Optimize data storage and retrieval for performance and scalability.
• Implement data governance, security and compliance best practices.
• Monitor and troubleshoot data pipeline issues.

Skills

Python

SQL

ETL/ELT

Data modeling

Data warehousing

Pandas

Spark

Cloud platforms

Education

Bachelor's degree in Computer Science / Data Engineering / Information Systems or related field

Tools

Pandas

Spark

Airflow

Job description

Flexjet is seeking a detail oriented AI Data Engineer to build and maintain data infrastructure that powers machine learning and AI systems. You will work closely with data scientists, ML engineers and software teams to ensure high quality, reliable and scalable data pipelines for AI applications.

The role involves designing and maintaining data pipelines for AI/ML workflows, collating clean data, and developing datasets for model training, validation and inference, while ensuring data quality