4Bell Technology

Job Description

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:

·         5+ years of experience in MLOps, DevOps, ML Engineering, or related roles.

·         Strong 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).