ML Ops Engineer

23 hours ago

New Delhi, India Wenger & Watson Full time

Experience - 5 - 10 yrsLocations - Bangalore, Chennai, Mumbai, Pune, Hyderabad Key Responsibilities Design, develop, and deploy machine learning models using AWS SageMaker for various business applications Implement end-to-end ML pipelines from data preprocessing to model serving and monitoring Build and maintain automated model training, validation, and deployment workflows Optimize model performance, scalability, and cost-effectiveness in production environments Create interactive ML applications and demos using Gradio for stakeholder demonstrations and user interfaces Develop robust Python applications for data processing, feature engineering, and model inference Build APIs and microservices for model serving and integration with existing systems Implement model versioning, A/B testing frameworks, and continuous integration/deployment practices ML infrastructure on AWS, including SageMaker endpoints, batch transform jobs, and processing jobs Monitor model performance, data drift, and system health in production environments Collaborate with DevOps teams to ensure reliable and scalable ML operations Implement security best practices for ML systems and data handlingTechnical Skills Expert-level proficiency in Python programming with strong software development practices Extensive hands-on experience with AWS SageMaker, including training jobs, endpoints, and pipelines Proven experience with Gradio for building ML application interfaces Strong background in machine learning algorithms, statistical modeling, and deep learning frameworks (PyTorch, TensorFlow, scikit-learn) Experience with MLOps practices, model versioning, and deployment strategies Deep understanding of AWS ecosystem (EC2, S3, Lambda, IAM, CloudFormation) Experience with containerization technologies (Docker, Kubernetes) Knowledge of data engineering tools and workflows (Apache Spark, Airflow, or similar) Familiarity with infrastructure as code and CI/CD pipelines Strong experience with version control systems (Git), code review processes, and agile development Excellent problem-solving skills and ability to debug complex distributed systems Experience with data visualization tools and techniques Strong communication skills for presenting technical concepts to diverse audiences

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