QUALIFICATIONS:

• Bachelor's degree in Computer Science, Engineering, or a related field. A Master's degree is preferred. 
• Experience in object-oriented programming and software architecture.
• Experience applying continuous delivery best practices, including CI/CD, Version Control, Trunk Based Development, Release Management, and Test-Driven Development using Python and SQL
• Proven experience in a presales or customer-facing role, preferably in the AI or MLOps domain. 
• Experience with popular MLOps tools (Kubeflow, mlflow, Tensor Flow Extended (TFX), AzureML, Google Cloud Machine Learning Engine, Domino Data Labs, Weights and Biases, Run:ai)
• Familiarity with AI technologies, including machine learning, deep learning, and natural language processing. 
• A deep understanding of MLOps principles and best practices, such as model deployment automation, model monitoring and logging, and model version control
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). 
• Excellent communication and presentation skills, with the ability to effectively convey complex technical concepts to both technical and non-technical audiences. 
• Strong problem-solving and analytical skills, with the ability to think creatively and propose innovative solutions. 
• Ability to work collaboratively in a fast-paced, dynamic environment and manage multiple projects simultaneously.