MLOps Engineer - Pune

Join a dynamic customer team as a hands-on MLOps Engineer and take ownership of designing, deploying, and automating comprehensive machine learning pipelines. This role offers a unique opportunity to operationalize cutting-edge ML solutions by leveraging your deep expertise in AWS services and MLOps best practices within a fast-paced, collaborative environment. We are seeking passionate professionals dedicated to clear communication and the development of impactful ML systems. This position is based in Pune, India.

Key Responsibilities

• Design, develop, and maintain robust ML pipelines for scalable production deployment.
• Implement and manage CI/CD workflows tailored for machine learning code and artifacts.
• Utilize core AWS services, with a significant focus on EKS, ECS, ECR, SageMaker (including processing, training, batch transform, hyperparameter tuning), Step Functions, EventBridge, SNS/SQS, and SageMaker Model Registry.
• Automate and orchestrate machine learning workflows to ensure reliability and reproducibility.
• Collaborate effectively with data scientists, engineers, and stakeholders to optimize ML models and deployment strategies.
• Monitor, troubleshoot, and enhance ML systems for peak performance, availability, and scalability.
• Maintain clear, concise, and comprehensive documentation for pipelines, deployments, and operational processes.

Required Skills and Qualifications

• Proven hands-on experience as an MLOps Engineer or in a similar role supporting live ML applications.
• Expertise in AWS cloud services, particularly EKS, ECS, ECR, SageMaker, Step Functions, EventBridge, SNS/SQS, and Model Registry.
• Deep understanding of core ML concepts and the complexities of deploying ML code in production-grade systems.
• Strong experience with MLFlow for experiment tracking and model management.
• Solid grasp of CI/CD concepts adapted for machine learning workflows.
• Exceptional written and verbal communication skills, with a strong emphasis on collaboration and documentation.
• Demonstrated ability to work on-site in Gurugram, Pune, or Bengaluru.

Preferred Qualifications

• Exposure to advanced ML workflow automation and monitoring tools.
• Previous experience in high-performance, large-scale ML environments.
• Relevant certifications in AWS or MLOps.