Python AI Engineer

Design & implement AI/ML solutions
Build end-to-end ML/AI pipelines: data ingestion, preprocessing, feature engineering, model training, evaluation, deployment and monitoring
Develop AI-powered applications and services using Python and modern ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn)
Work on advanced AI use cases — from classical ML to deep learning, NLP, computer vision, or generative AI / LLM-based solutions depending on business needs
Write clean, modular, well-tested Python code for AI services; ensure code quality, maintainability, and reliability
Package and deploy ML/AI services via microservices or APIs (e.g. RESTful APIs), leveraging containerization (e.g., Docker) and cloud or on-prem infrastructure
Define, build, and maintain MLOps pipelines: CI/CD for models and services, automated testing & validation, version control, model serving, monitoring and lifecycle management
Architect scalable, robust, and maintainable ML/AI systems — including data pipelines, model serving, inference services, and integration with other business systems
Optimize model performance (training & inference), resource usage, latency, and reliability — ensuring AI systems meet production-grade standards