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.