MLOps 3 years experience Immediate joiner

MLOps Engineer

Job Details

Location: Mumbai

Experience Required: 2 to 4 Years

Employment Type: Full-Time

About the Role

We are looking for a motivated MLOps Engineer to join our growing AI/ML team. In this role, you will support and build ML pipelines, assist in model deployment, and contribute to the automation of the machine learning lifecycle. This is an excellent opportunity to grow within a high-impact fintech environment.

Key Skills / Keywords

MLOps, MLFlow, Python, Docker, Jenkins, Kubernetes, Automation, SDLC, Deployment

Key Responsibilities

• Assist in the design and development of MLOps pipelines for deployment and integration of ML models.
• Support data scientists and senior engineers in operationalizing machine learning models.
• Automate model training, testing, and deployment workflows using Python and shell scripting.
• Monitor models in production and flag performance issues or anomalies for resolution.
• Implement and maintain version control practices for ML models and data.
• Containerize ML services and applications using Docker.
• Set up and maintain Jenkins pipelines for continuous integration and delivery.

Support Kubernetes-based deployment of ML workloads.

• Ensure adherence to security, data privacy, and governance standards.
• Document MLOps processes, workflows, and configurations for team knowledge sharing.
• Stay current with emerging MLOps tools, frameworks, and best practices.
• Participate in sprint planning, standups, and retrospectives in an Agile environment.

Required Skills s Experience

• 2–4 years of experience in MLOps, DevOps, or software engineering with ML exposure.
• Hands-on experience or strong familiarity with MLFlow.
• Proficiency in Python; experience with automation and Shell/Bash scripting.
• Working knowledge of Docker for containerization.
• Experience with Jenkins or similar CI/CD tools.
• Basic understanding of Kubernetes for container orchestration.
• Understanding of machine learning concepts and the model development lifecycle.
• Familiarity with SDLC practices and Agile methodologies.
• Good analytical and problem-solving skills.
• Strong communication skills and ability to work collaboratively in a team.
• Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field.