Responsibilities :- Convert Python-based ML code to C++ working programs for deployment on various platforms.- Ensure code quality through static and dynamic checks, adhering to software development best practices.- Cross-compile code for different platforms, optimizing performance and compatibility.- Convert ML models to edge-friendly formats, such as TensorFlow Lite, for efficient deployment on edge devices.- Utilize Docker for containerization, enabling seamless deployment and management of ML applications.Requirements :- Intermediate level knowledge of Python and C++, with the ability to develop and maintain code in both languages.- Understanding of ML modeling issues and processes, with the ability to deploy ML models effectively.- Strong experience in deploying ML models on both cloud and edge devices, with a focus on optimization and efficiency.- Proficiency in converting Python ML code to C++, ensuring compatibility and performance.- Familiarity with code quality checks and software development processes, ensuring robust and reliable deployments.- Knowledge of cross-compilation techniques and converting ML models to edge-friendly formats for efficient deployment.- Experience with Docker for creating and using containers, facilitating the deployment and management of ML applications.- If you are passionate about machine learning deployment and have the skills and experience outlined above, we encourage you to apply. Join us in shaping the future of ML deployment on cloud and edge devices. (ref:hirist.tech)