Hiring For MLops Engineer

Required Skills

• Strong programming skills in Python.
• Hands-on experience with MLOps pipelines and machine learning lifecycle management.
• Experience with Docker and Kubernetes.
• Knowledge of CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
• Experience with MLflow, Kubeflow, Airflow, or equivalent orchestration and lifecycle tools.
• Knowledge of cloud-based ML services such as AWS SageMaker, Azure Machine Learning, or Google Vertex AI.
• Understanding of REST APIs, model serving, automated testing, and deployment strategies.
• Familiarity with Git, Linux, and infrastructure-as-code tools.
• Understanding of model monitoring, data quality, model drift, and performance optimization.

Good to Have

• Experience with feature stores and model registries.
• Knowledge of PyTorch, TensorFlow, or Scikit-learn.
• Experience with LLMOps, GenAI deployment, and LLM monitoring.
• Familiarity with Spark, Kafka, and large-scale data processing.
• Experience with security, governance, and compliance in production ML systems