Responsibilities
- Develop, maintain, and deploy Python-based production services
- Build and operate ML pipelines and MLOps infrastructure
- Work with AWS services including Lambda, Step Functions, DynamoDB, Kafka, and containerized applications
- Deploy, monitor, and maintain ML models (e.g., XGBoost) in production environments
- Ensure reliability, correctness, and performance of AI systems
- Ship code to production frequently (daily or near-daily)
- Debug and resolve production issues efficiently
- Collaborate with data scientists, product managers, and operational teams to support AI-driven products
Basic qualifications
- Experience with Python (production-quality code)
- Hands-on AWS experience (Lambda, Step Functions, DynamoDB, IAM, containers)
- Experience with Kafka or other event-driven systems
- Experience deploying ML models to production
- Git / CI/CD experience
Preferred qualifications
- Experience with MLOps platforms and automation tools
- Real-time data pipelines
- Experience with AI chatbots or retrieval-augmented generation (RAG) systems
Tags & focus areas
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