Backend Engineer (MLOps Platform | Python + AWS)_Backend Engineer_3+yrs

Job Description

The role involves building backend components for an MLOps platform on AWS. You will design and develop backend services that support feature engineering, feature serving, model deployment, and inference for both batch and real-time systems. The job requires close collaboration with global cross-functional teams and participation in an on-call rotation to handle production incidents. Core responsibilities include backend API development, cloud-based service integration, automation, and maintaining reliable, scalable infrastructure for ML workflows. ? Important Key Skill Set (Must-Have) Backend Engineering Strong Python development (3+ years) Backend frameworks: Flask / Django / FastAPI Web servers: Gunicorn, Uvicorn Understanding of ASGI/WSGI Concurrency & Performance AsyncIO Concurrent programming concepts Cloud Skills Experience with AWS (preferred) Lambda API Gateway S3 CloudWatch Testing & CI/CD Unit & functional testing frameworks CI/CD systems (Jenkins, GitHub Actions, GitLab CI) ? Important Key Skill Set (Nice-to-Have) MLOps & Data Experience with AWS SageMaker, Kubeflow, MLflow Exposure to model deployment & inference pipelines Big data tools: Apache Spark Streaming/Data Pipelines Apache Kafka (Python client apps) DevOps Docker, ECS/EKS Infrastructure as Code: Terraform Python Packaging Wheel, PEX, Conda environments ?? One-Line Summary of Ideal Candidate A Python backend engineer with strong AWS experience, proficiency in FastAPI/Flask, AsyncIO, CI/CD pipelines, and exposure to MLOps tools like SageMaker or MLflow. Skills: python,docker,kubernetes,terraform,aws