Machine Learning Specialist

About the role
This role will ensure the efficient deployment and maintenance of advanced analytics models, information products, and code assets by developing and supporting continuous integration and delivery (CI/CD) pipelines for digital solutions.
The role collaborates closely with Data Scientists and Developers to create, manage, and support streamlined end-to-end deployment processes, ensuring stable performance and long-term efficiency.
Responsibilities
Create, implement, test, and maintain automated CI/CD pipelines for machine learning models and advanced analytics products, with a focus on ensuring high quality, dependability, and scalability.
Identify opportunities for automation to enhance business processes, drive innovation, and support scalability.
Keep current with the latest trends and technologies in MLOps and related fields, and implement best practices to benefit the team.
Create and maintain documentation for deployment pipelines, processes, and solutions using tools like Confluence and GitHub to ensure transparency and accountability.
Address and resolve issues with machine learning models and related deployment infrastructure as they occur.
Skills and experience
In-depth knowledge of Machine Learning (ML) and Artificial Intelligence (AI) concepts, terminology, and techniques, including supervised and unsupervised learning, deep learning, natural language processing, and large language models.
Proficiency in programming languages like Python or R, with experience using code libraries such as TensorFlow, PyTorch, and scikit-learn.
Familiarity with cloud computing and analytics platforms like Databricks, AWS, and Azure, including experience with their native services and deploying machine learning models on these platforms.
Experience with MLOps tools and techniques, including automated testing and monitoring methods.
Experience with cloud deployment and containerization frameworks like Docker and Kubernetes.

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