Python ML Backend Engineer

Technology Stack Requirements
o        Backend: Python (Django, FastAPl)
Unit/integration testing (pytest)
Asynchronous job scheduling (Celery)
Adherence to PEP8 and PEP257 coding standards
Frontend: ReactJS (Next.js)
Machine Learning:
Python ML & DS ecosystem (PyTorch, XGBoost, scikit-learn, pandas, numpy)
Model interpretability & explainability frameworks (SHAP)
ML pipelines & workflow automation (MLflow, Airflow)
Infrastructure: AWS (EC2, S3, EKS, SageMaker)
Infrastructure as Code (laC) using Terraform and Ansible
Proper IAM role-based access controls
Network security best practices (VPC, security groups, private subnets)
MLOps:
Model training, monitoring, & deployment (MLflow, AWS SageMaker, AWS Airflow)
Data labeling & versioning (Label Studio, DVC
CH/CD & Monitoring:
Automated linting, test & deployment: Jenkins
Telemetry & Monitoring: Prometheus, Grafana, AWS CloudWatch
Containerization & Orchestration: Docker