Summary

Requirements

• 3 years of experience in software engineering, DevOps, or ML engineering.
• Strong proficiency with Python and experience in containerization (Docker, Kubernetes).
• Familiarity with cloud platforms such as AWS, GCP, or Azure.
• Experience deploying machine learning models using frameworks such as TensorFlow, PyTorch, or ONNX.
• Knowledge of CI/CD pipelines and infrastructure-as-code tools (Terraform, Helm, etc.).
• Understanding of MLOps concepts and best practices for AI deployment and monitoring.
• Excellent communication skills and ability to work in a fast-paced, collaborative environment.

Nice to Have

• Experience with model serving frameworks (e.g., FastAPI, TorchServe, BentoML).
• Familiarity with monitoring tools (Prometheus, Grafana, ELK Stack).
• Background in AI/ML performance optimization and distributed computing.
• Interest in LLM-based systems and agentic AI architectures.