Sr Lead AI Data Engineer - 100% onsite work and onsite interview

        Bachelor''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''s degree in Computer Science, Data Science, Engineering, or a related field

     15+ years of experience in software or data engineering, with at least 4 years focused on ML systems or MLOps in a production environment.

        Demonstrated experience building or operating a shared/enterprise ML platform serving multiple teams or business units.

        Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).

        Hands-on experience with MLOps tooling: Kubeflow, MLflow, Airflow, or equivalent.

        Experience with cloud-native data and ML services on AWS.

        Working knowledge of LLMs, prompt engineering, and RAG architecture patterns.

        Experience with containerization and orchestration (Docker, Kubernetes).

        Strong understanding of data engineering concepts: pipelines, feature stores, data quality, and lineage.