Demonstrated experience leading and implementing AI/ML projects from ideation to delivery, evaluation, and maintenance in production Hands on familiarity with Python and one of PySpark or Scala, including demonstrable proficiency of AI/ML frameworks and tools (e.g., MLFlow, TensorFLow, PyTorch) Working knowledge of Software Development tools and practices including DevOps and CI/CD tools (e.g., Git, Jenkins, Docker, Kubernetes, etc.) Familiarity with data versioning tools (Delta Lake, DVC, LakeFS, etc.) Familiarity with model observability tools for insights into the behavior, performance, and health of your deployed ML models (tracking, alerting, compliance monitoring, etc.) Demonstrable proficiency in cloud platforms and services (Azure, AWS, GCP, etc.) Demonstrable proficiency in Gen AI solution pipeline engineering, RAG, Evaluations Demonstrable proficiency in Large Language Modeling and Transformer Architectures (BERT, GPT, etc.) Demonstrable proficiency in AI/ML engineering systems with Python Demonstrable proficiency of AI/ML frameworks and tools (MLFlow, TensorFLow, PyTorch, JAX)