AI Data Engineer (US)

About the Role

We are looking for an experienced AI Data Engineer to build scalable data pipelines, cloud-based data platforms, and high-quality datasets that power modern AI and machine learning applications. The ideal candidate has strong expertise in Python and SQL, solid data engineering fundamentals, and hands-on experience with cloud technologies and ML workflows.

Responsibilities

• Design, develop, and maintain scalable ETL/ELT and data pipelines.
• Build and optimize data infrastructure supporting AI/ML applications.
• Develop reliable data processing solutions using Python and SQL.
• Integrate data from databases, APIs, applications, and other sources.
• Design data models, data warehouses, and analytics-ready datasets.
• Prepare, transform, validate, and optimize datasets for machine learning.
• Collaborate with Data Scientists, ML Engineers, Software Engineers, and business teams.
• Implement data quality, monitoring, governance, and security best practices.
• Optimize data pipelines and cloud infrastructure for performance, scalability, and reliability.
• Support ML model training, deployment, and production data workflows.
• Troubleshoot data and pipeline issues and continuously improve system performance.

Required Qualifications

• 2–7 years of experience in Data Engineering, AI/ML Engineering, or a related field.
• Strong hands-on experience with Python and SQL.
• Solid understanding of data engineering, data modeling, ETL/ELT, and data warehousing.
• Working knowledge of machine learning concepts and AI data workflows.
• Experience with at least one major cloud platform: AWS, Azure, or Google Cloud.
• Experience working with relational and analytical databases.
• Strong understanding of data integration, APIs, and distributed data processing.
• Ability to work effectively in a collaborative, fast-paced environment.

Preferred Qualifications

• Experience with Apache Spark, Databricks, Airflow, Kafka, or similar technologies.
• Experience with Snowflake, BigQuery, Redshift, or other modern data warehouses.
• Knowledge of GenAI, LLM, RAG, vector databases, or AI application pipelines.
• Experience with Docker, Kubernetes, CI/CD, and cloud infrastructure.
• Familiarity with MLOps and production machine learning systems.
• Experience building highly scalable and reliable cloud data platforms.

Benefits

• Competitive salary: $115K–$195K+
• Health, dental, and vision benefits
• 401(k) and retirement benefits
• Paid time off and holidays
• Professional development opportunities
• Flexible/hybrid work options, depending on role and location
• Opportunity to work with modern AI, ML, data, and cloud technologies

Skills

cloud, data engineering, ml, python