AI Data Engineer

5-7 years of hands-on experience in data engineering, with at least 2 years focused on AI/ML workloads.
Expert proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn.
Strong experience with Databricks, Apache Spark, and distributed computing for ML workflows.
Deep understanding of the machine learning lifecycle, including model training, deployment, and monitoring processes.
Experience with feature engineering, data preprocessing techniques, and ML data pipelines.
Knowledge of vector databases, embeddings, and similarity search for AI applications.
Proficiency in SQL for structured and unstructured data management.