Python Developer (AI/ML Focus) – Checkout Systems

Overview

We’re looking for a Python Developer with hands-on exposure to AI/ML to support high-impact checkout initiatives within a digital commerce environment. This role focuses on building intelligent backend services that improve checkout performance, enable real-time decisioning, and enhance customer experience through automation and predictive analytics.

What You’ll Do

• Design and develop scalable Python-based microservices powering checkout workflows
• Build intelligent systems for:
  • Checkout optimization and performance improvement
  • Failure prediction and automated retry handling
  • Transaction anomaly and fraud detection
• Integrate AI/ML-driven insights into cart, payment, and order processing systems
• Develop and expose APIs for real-time model inference and decision-making
• Collaborate with backend teams (Java and others) for seamless end-to-end integration
• Analyze large datasets to identify drop-offs and improve conversion rates
• Ensure high system reliability, performance, and scalability
• Troubleshoot production issues, perform RCA, and drive continuous improvements

Required Skills

• Strong programming experience in Python (3.x)
• Experience building RESTful APIs using Flask, FastAPI, or Django
• Solid understanding of microservices architecture
• Exposure to AI/ML concepts and model integration
• Hands-on experience with data libraries such as Pandas and NumPy
• Familiarity with ML frameworks like scikit-learn, TensorFlow, or PyTorch
• Experience working with large datasets and data processing pipelines
• Knowledge of SQL and/or NoSQL databases
• Strong debugging, problem-solving, and analytical skills

Nice to Have

• Experience in e-commerce or telecom checkout systems
• Exposure to LLMs / Generative AI use cases
• Understanding of MLOps and model deployment pipelines
• Experience with Kafka or real-time streaming systems
• Familiarity with cloud platforms (AWS, Azure, or Google Cloud Platform)
• Knowledge of A/B testing and experimentation frameworks