Job Description Collaborate closely with cross-functional teams, including Data Scientists, Data Engineers, and Cloud App Development Engineers, to ensure seamless integration of machine learning solutions into broader systems. Lead the activation of new machine learning models, overseeing the deployment process from development to production environments. Implement and adhere to MLOps best practices, ensuring the reliability, scalability, and maintainability of machine learning workflows. Manage and optimize Azure DevOps release pipelines, orchestrating the end-to-end deployment process for machine learning models. Utilize PySpark and associated libraries to develop and optimize data processing workflows, ensuring efficient handling of large-scale datasets. Proactively identify and address challenges related to model deployment, system integration, and data processing, working collaboratively to find effective solutions. Requirements At least 1-2+ years of hands-on experience with MLOps, demonstrating proficiency in deploying and managing machine learning models in production environments. Hands-on experience using PySpark and associated libraries for scalable and distributed data processing in the context of machine learning workflows. Proven experience with Azure DevOps release pipelines, showcasing expertise in continuous integration, continuous deployment, and version control for machine learning projects. Proficiency in the Python programming language, with a focus on its application in machine learning development and deployment. Practical experience in machine learning, including a deep understanding of ML algorithms and feature engineering techniques. Programming knowledge in MS SQL, demonstrating the ability to work with and manipulate data within relational databases.
Senior Lead MLOps Engineer in Constanţa
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