The company is seeking an AI Data Engineer to design, build, and maintain data infrastructure that powers AI and machine learning applications, bridging traditional data engineering with AI-specific needs to ensure high-quality, scalable data pipelines for advanced analytics and model deployment. This role is crucial in managing all incoming data for Health & Welfare (H&W) clients, setting up inbound files, ensuring seamless integration, and maintaining data integrity.
Requirements
- Proficiency in Python, SQL, and data pipeline frameworks like Airflow and dbt.
- Experience with big data tools such as Spark, Kafka, and Hadoop.
- Familiarity with ML tools and frameworks like TensorFlow and PyTorch.
- Knowledge of vector databases and LLM pipelines is a plus.
- Proficient grasp of data modeling, statistics, and machine learning principles.
- Machine learning
- Python
Responsibilities
- design, build, and maintain data infrastructure that powers AI and machine learning applications
- ensuring high-quality, scalable data pipelines that support advanced analytics and model deployment
- setting up inbound files from clients and vendors
- ensuring seamless integration into the H&W platform
- maintaining data integrity throughout the process
- Machine learning
- Python
Other
- AI Engineer - This is the goal but we cannot afford the real skillset.
- Data is the primary focus
- Experience with machine learning models and integrating with AI
- Dashboard experience with power BI
- Outstanding problem-solving and analytical thinking.
