This role requires 4 days per week in-office at our Cleveland Headquarters, 747 Alpha Drive, Highland Heights, OH 44143

BASIC QUALIFICATIONS:

• Bachelor’s degree or higher in Computer Science, AI, Data Science, or a related field, or equivalent experience.
• 3+ years of hands-on experience developing and deploying AI/machine learning solutions.
• Proficiency in Python programming (Spark, pandas, etc.) and SQL.
• Solid understanding of AI methodologies, including supervised/unsupervised learning, regression analysis, and neural networks.
• Practical knowledge of cloud platforms, particularly Azure (Azure Synapse, Azure ML, Azure Data Factory, Azure Functions).
• Experience with Visual Studio, Git, and Azure DevOps.
• Familiarity with software development fundamentals such as SOLID principles, Object-Oriented design, DRY, and Domain Driven Design.
• Strong communication skills, both written and verbal.

PREFERRED QUALIFICATIONS:

• Knowledge of Vibe Coding and familiarity with cutting-edge industry trends.
• Microsoft Cloud Certification.
• Experience with technologies such as Azure Databricks, Cosmos DB, CQRS Pattern, Dependency Injection, Entity Framework & LINQ, Microservices, OData, and asynchronous programming.
• Exposure to Agile methodologies and Test Driven Development (TDD).

• Design, develop, and deploy scalable AI models and algorithms aligned with business objectives.
• Develop high-performing, reusable, and reliable code following industry standards and best practices.
• Participate in all phases of the Software Development Life Cycle (SDLC), including requirement gathering, design, implementation, testing, deployment, documentation, and support.
• Build machine learning pipelines leveraging tools such as Python, Spark, Azure ML, and OpenAI.
• Collaborate with data analysts, data engineers, software engineers, and business analysts to translate complex business requirements into technical solutions.
• Employ Azure DevOps and Git to ensure proper version control and adherence to CI/CD best practices.
• Troubleshoot, analyze, and resolve AI model performance issues and production problems.
• Maintain up-to-date knowledge of advancements in AI, machine learning, and data engineering.
• Actively participate in team meetings, contributing ideas and insights to drive continuous improvement.
• Demonstrate strong problem-solving skills, excellent work ethic, and proactive attitude.