Machine Learning Engineer

Job Title: MLOps Engineer

Job Type: Full-time(8hours/day) Contract

Location: Hybrid – Gurugram

Job Summary:

We are seeking an experienced MLOps Engineer to join our customer's team in a hybrid role based in Gurugram. You will play a pivotal role in enabling seamless model development, deployment, and monitoring, collaborating directly with clients and stakeholders to deliver robust AI solutions.

Key Responsibilities:

• Design, implement, and manage the end-to-end MLOps pipeline, including model development, deployment, versioning, and monitoring.

• Leverage AWS services such as SageMaker, Lambda, S3, CodeBuild, CodeCommit, and Step Functions for scalable model operations.

• Integrate CI/CD and DevOps best practices into machine learning workflows to enhance automation and reliability.

• Containerize ML applications using Docker, and orchestrate deployments with EKS and ECR.

• Deploy user interfaces (UIs) for ML solutions on EC2 and EKS in line with microservices architecture.

• Collaborate closely with clients, providing daily updates and clear technical communication.

• Troubleshoot and resolve any deployment or operational issues, ensuring optimal performance of ML solutions.

Required Skills and Qualifications:

• 4+ years of experience in MLOps, DevOps, or a related field.

• In-depth understanding of the MLOps framework covering model lifecycle management.

• Proven hands-on experience with AWS SageMaker, CodeBuild, CodeCommit, S3, Lambda, and Step Functions.

• Solid experience with containerization using Docker, Kubernetes (EKS), and ECR.

• Familiarity with CI/CD pipelines and automation tools.

• Background in deploying UIs for ML applications on cloud infrastructure.

• Exceptional written and verbal communication skills, with a strong client-facing presence.

Preferred Qualifications:

• Prior experience orchestrating ML workflows with Step Functions.

• Exposure to microservices architectures and modern deployment strategies.

• Experience working in fast-paced, client-driven environments with daily reporting.