We are looking for a highly skilled Senior MLOps Engineer with 4+ years of experience to design, build, and optimize scalable machine learning infrastructure. The ideal candidate will work closely with Data Scientists, ML Engineers, and DevOps teams to deploy, monitor, and scale ML models in production environments.

Key Responsibilities:

- Design, implement, and manage end-to-end ML pipelines (training, validation, deployment, monitoring).

- Deploy machine learning models into production using CI/CD best practices.

- Build and maintain scalable MLOps infrastructure on cloud platforms (AWS, Azure, or GCP).

- Automate model training, versioning, testing, and deployment workflows.

- Implement model monitoring for performance, drift, data quality, and retraining triggers.

- Collaborate with data science teams to productionize ML models efficiently.

- Manage containerized ML workloads using Docker and Kubernetes.

- Ensure security, reliability, scalability, and high availability of ML systems.





- Troubleshoot production issues and optimize model performance.

Required Skills & Qualifications:

- 4+ years of experience in MLOps, DevOps, ML Engineering, or related roles.

- Solid programming skills in Python.

- Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

- Experience with CI/CD tools (GitHub Actions, GitLab CI, Jenkins, Azure DevOps).

- Strong expertise in Docker and Kubernetes.

- Experience working with cloud platforms: AWS / Azure / GCP.

- Knowledge of model versioning and experiment tracking tools (MLflow, Weights & Biases, Kubeflow).

- Strong understanding of data pipelines, ETL processes, and APIs.

- Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK).

- Good understanding of software engineering best practices, distributed systems, and system design.

📌 MLOps Engineer (Bengaluru)
🏢 Infoobjects
📍 Bengaluru