Minimum qualifications:

• Bachelor's degree or equivalent practical experience.
  
• 8 years of experience in virtualization or cloud native architectures in a customer-facing or support role.
  
• Experience with big data and machine learning frameworks such as Tensorflow, PyTorch or scikit-learn, along with implementing Machine Learning Operations at enterprise scale, on any cloud platform.
  
• Experience engaging with, and presenting to, technical stakeholders and executive leaders.
  

Preferred qualifications:

• Experience with building Machine Learning (ML) Solutions, Machine Learning Operations frameworks like kubeflow, and leveraging specific machine learning architectures (e.g., deep learning, LSTM, convolutional networks, etc.).
  
• Experience in understanding a complex customer’s existing software workloads and the ability to define a technical migration roadmap to the Cloud reflecting specific customer needs.
  
• Experience in building and deploying data and ML pipelines with a focus on automation.
  
• Familiarity with machine learning programming frameworks such as LangChain, PyTorch, HuggingFace, and Tensorflow.
  
• Familiarity with prompt tuning and experience delivering successful prototypes.