Senior MLOps Engineer

Senior MLOps Engineer Job Description : Must-Have Skills : - Strong proficiency in Python/PySpark, especially in analytical contexts. - DevOps and CI/CD expertise with Git proficiency. - Ability to build and maintain CI/CD pipelines. - Code refactoring skills and knowledge of software development principles (OOPs, SOLID). - Unit testing and exception handling expertise. - Deep understanding of ML techniques and their applications. - End-to-end ML lifecycle experience. - Experience with model deployment and cloud services. - Model monitoring and drift detection capabilities. - Knowledge to develop production-ready code implementations. - Knowledge of unsupervised & unsupervised learning techniques (Regression, Classification, clustering, etc). - SQL proficiency. Good To Have Skills : - Experience in the CPG/Retail domain. - Cloud computing and big data technologies expertise. - Experience with containerization and deployment of ML models. - Familiarity with MLOps-specific tools. - Experience with data visualization and data imputation techniques. - Background in software development practices and agile methodologies. - Experience automating model testing and validation processes. Responsibilities : MLOps Pipeline Development and Maintenance : - Design, build, and maintain CI/CD pipelines for machine learning models. - Automate model deployment, monitoring, and drift detection processes. - Implement and manage containerization and orchestration of ML models. ML Model Deployment and Cloud Services : - Deploy and manage ML models on cloud platforms (AWS, Azure, GCP). - Utilize cloud-based services for model serving and scaling. Data Engineering and Processing : - Develop and maintain data processing pipelines using Python/PySpark. - Perform data cleaning, transformation, and feature engineering. - Utilize SQL for data querying and manipulation. Software Development and Code Quality : - Write clean, efficient, and maintainable code following OOPs and SOLID principles. - Perform code refactoring and ensure code quality. - Implement unit testing and exception handling. - Develop production-ready code implementations. Machine Learning Techniques and Applications : - Apply deep understanding of supervised and unsupervised learning techniques (Regression, Classification, Clustering, etc.). - Implement model monitoring and drift detection capabilities. - Develop and implement ML techniques for business applications. Model Testing and Validation : - Automate model testing and validation processes. - Ensure model accuracy and reliability. Collaboration and Communication : - Collaborate with data scientists, data engineers, and architects. - Communicate effectively with cross-functional teams. - Create and maintain technical documentation. Soft Skills : - Strong communication skills to collaborate with data scientists, data engineers, and architects. - Problem-solving abilities and analytical thinking. - Attention to detail, especially for audit-ready code. - Ability to work in cross-functional teams. - Technical documentation capabilities. (ref:hirist.tech)

Location: bangalore, IN

Posted Date: 5/1/2025