Description

You will build and maintain backend services and machine learning pipelines.

Responsibilities

• Develop backend services using Python, Django, and FastAPI.
• Build and automate ML pipelines and workflows using MLflow and Airflow.
• Manage model training, monitoring, and deployment via AWS SageMaker.
• Implement infrastructure as code using Terraform and Ansible.
• Ensure system security through IAM role-based access controls and network security best practices.

Required Skills

• 7+ years of professional experience.
• Proficiency in Python and the ML/DS ecosystem (PyTorch, XGBoost, scikit-learn, pandas, numpy).
• Experience with Django and FastAPI.
• Hands-on with AWS services including EC2, S3, EKS, and SageMaker.
• Strong knowledge of MLflow and Airflow for pipeline automation.
• Experience with Docker for containerization.
• Competency in unit and integration testing using pytest.
• Familiarity with CI/CD via Jenkins and automated linting.
• Understanding of model interpretability frameworks like SHAP.
• Knowledge of telemetry and monitoring tools such as Prometheus, Grafana, and AWS CloudWatch.
• Experience with data labeling and versioning using Label Studio and DVC.

Preferred Skills

• Experience with ReactJS and Next.js for frontend integration.
• Knowledge of asynchronous job scheduling with Celery.

Key Skills

Education

Any Gradute