Azure Python ML Engineer

As an ideal candidate for the role, you should have the following technical skills: - Advanced Python: You should be well-versed in class-based design, modular architecture, and reusable components. Your development approach should not be limited to "script-only" or notebook-centric methodologies. - API Development: Proficiency in developing RESTful services and optimizing endpoint performance is essential. Experience with OpenAPI / Swagger documentation is a plus. - Async Programming: Familiarity with async/await, concurrency, and threading for I/O-heavy workloads is necessary to effectively handle asynchronous tasks. - CI/CD: Experience with Azure Pipelines and/or GitHub Actions is required. You should have the ability to evolve pipelines rather than just utilizing existing ones. - Data & ML: Knowledge of Pandas / Polars and Scikit-Learn is important for data manipulation and machine learning tasks. - Testing: Proficiency in PyTest is expected, along with a strong emphasis on automated testing as a quality assurance measure. - Schema-Driven Development: Understanding and experience with JSON schemas for configuration, workflow parameters, and APIs is crucial. You should be capable of updating and managing schema evolution efficiently. If you possess these technical skills, you are well-equipped to excel in this role. As an ideal candidate for the role, you should have the following technical skills: - Advanced Python: You should be well-versed in class-based design, modular architecture, and reusable components. Your development approach should not be limited to "script-only" or notebook-centric methodologies. - API Development: Proficiency in developing RESTful services and optimizing endpoint performance is essential. Experience with OpenAPI / Swagger documentation is a plus. - Async Programming: Familiarity with async/await, concurrency, and threading for I/O-heavy workloads is necessary to effectively handle asynchronous tasks. - CI/CD: Experience with Azure Pipelines and/or GitHub Actions is required. You should have the ability to evolve pipelines rather than just utilizing existing ones. - Data & ML: Knowledge of Pandas / Polars and Scikit-Learn is important for data manipulation and machine learning tasks. - Testing: Proficiency in PyTest is expected, along with a strong emphasis on automated testing as a quality assurance measure. - Schema-Driven Development: Understanding and experience with JSON schemas for configuration, workflow parameters, and APIs is crucial. You should be capable of updating and managing schema evolution efficiently. If you possess these technical skills, you are well-equipped to excel in this role.