Job
Description
Job Title: MLOps Engineer Locations: Hyderabad/Bnglr/Chennai/Mumbai/Pune/Kolkata/Gurgaon Job Description: We are seeking a highly skilled Senior MLOps Engineer with 4-10 yrs years of experience to join our team. The ideal candidate will have extensive expertise in model deployment, model monitoring, and productionizing machine learning models. Candidate will play a crucial role in designing and implementing efficient workflows for ML programming and team communication, ensuring seamless integration of ML solutions within our organization. Key Responsibilities: Model Deployment: Manage and optimize model deployment processes, including the use of Kubernetes for containerized model deployment and orchestration. Model Registry Management: Maintain and manage a model registry to track versions and ensure smooth transitions from development to production. Design, develop, and maintain robust ETL/ELT, curated and feature engineering processes using Python and SQL to extract, transform, and load data from various sources into our data platforms CI/CD Implementation: Develop and implement Continuous Integration/Continuous Deployment (CI/CD) pipelines for model training, testing, and deployment, ensuring high code quality through rigorous model code reviews. Model Monitoring & Optimization: Design and implement model inference pipelines and monitoring frameworks to support thousands of models across various pods, optimizing execution times and resource usage. ¢ Team Leadership & Training: Manage, mentor, and train junior engineers, fostering their growth and learning while overseeing a large team ¢ Collaboration with Data Science Teams: Train and collaborate with data science team members on best practices in tools such as Kubeflow, Jenkins, Docker, and Kubernetes to ensure smooth model productionization. ¢ Reusable Frameworks Development: Draft designs and apply reusable frameworks for drift detection, live inference, and API integration. ¢ Cost Optimization Initiatives: Propose and implement strategies to reduce operational costs, including optimizing models for resource efficiency, resulting in significant annual savings. ¢ Documentation & Standards Development: Produce MLE standards documents to assist data science teams in deploying their models effectively and consistently. Qualification: Education: Bachelors degree in Computer Science, Information Technology, Engineering, or a related field. Experience: 4-10 years of experience in data engineering or a related field, with a strong focus on Python, SQL, and Azure Cloud technologies. Technical Skills: Proficiency in advanced Python for model deployment, data manipulation, automation, and scripting. Proficient in Kubernetes, model monitoring, and CI/CD practices Productionizing machine learning models, Experience with programming languages and ML frameworks (e.g., TensorFlow, PyTorch). Advanced SQL skills for complex query writing, optimization, and database management. Experience with big data technologies (e.g., Spark, Hadoop) and data lake architectures. Familiarity with CI/CD pipelines, version control (Git), and containerization (Docker), Airflow is a plus. Soft Skills: Strong problem-solving and analytical skills. Excellent communication and collaboration abilities. Ability to work independently and as part of a team in a fast-paced environment.
