AI_ML_ Engineering - LEAD

AI_ML_ Engineering  -  LEAD

In-Person Interview

• Bachelor''''s degree in Computer Science, Data Science, Engineering, or a related field (Master''''s preferred).
• 16+ years of experience in software or data engineering, with at least 3 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.