AI/ML Engineer - Deep Learning

AI / ML Engineer (MLOps) :Location : Bengaluru

Experience : 5+ Years

Job Summary :

We are looking for an experienced AI/ML Engineer with strong expertise in Machine Learning Operations (MLOps) to build, deploy, and manage production-ready machine learning systems. The ideal candidate will have hands-on experience in designing scalable ML pipelines, deploying models, implementing CI/CD workflows, and managing the end-to-end machine learning lifecycle.

Key Responsibilities :

• Design, develop, and maintain scalable machine learning pipelines to support AI initiatives.

• Build and deploy production-ready machine learning models using cloud AI services and modern MLOps practices.

• Containerize and deploy models using Docker and FastAPI for real-time and batch inference.

• Implement and manage CI/CD pipelines for ML workflows using tools such as GitHub Actions.

• Manage the complete model lifecycle, including versioning, packaging, registration, and governance using MLflow or similar tools.

• Monitor model performance, data drift, and system health, and proactively optimize models to ensure accuracy and efficiency.

• Collaborate with cross-functional teams and contribute to key technical decisions.

• Mentor junior team members and drive best practices across projects.

Required Skills :

• Strong expertise in Machine Learning Operations (MLOps).

• Advanced Python programming skills.

• Hands-on experience with ML pipeline development and deployment.

• Experience with Docker, FastAPI, and containerized deployments.

• Strong knowledge of CI/CD automation and workflow orchestration.

• Mandatory experience with MLflow and Airflow.

• Good exposure to cloud platforms and AI services.

• Thorough understanding of infrastructure requirements for MLOps implementation.

• Experience with machine learning frameworks and production environments.

• Multi-cloud experience is highly preferred.

Preferred Qualifications :

• Minimum 5 years of experience in Machine Learning Operations.

• Strong analytical and problem-solving skills.

• Ability to work in a collaborative and fast-paced environment.

• Experience in monitoring, optimizing, and scaling machine learning systems.