ML Ops Engineer

Experience - 5 - 10 yrs

Locations - 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 handling

Technical 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