Required:
· 5+ years of experience in AI/ML engineering with a strong focus on generative AI, RAG applications, and predictive modeling.
· Proficiency in Python and AI/ML libraries like TensorFlow, PyTorch, and Scikit-Learn.
· Hands-on experience with LLMs, NLP models, prompt engineering, and tools like OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, and AI agentic frameworks.
· Strong understanding of data preprocessing, feature engineering, and model selection for time series and pricing data.
· Experience in building and deploying ML models on cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
· Knowledge of MLOps best practices, including CI/CD pipelines, version control, and model monitoring.
· Excellent problem-solving skills and ability to communicate complex AI concepts clearly.
Preferred:
· Experience with AI-driven pricing optimization in retail, logistics, or e-commerce.
· Experience developing and deploying RAG systems for dynamic content retrieval.
· Familiarity with AI agentic frameworks for building autonomous AI agents.
· Prior work in AI automation for supply chain, demand forecasting, or pricing strategies.
· Strong knowledge of AI/ML ethics, ensuring fairness and bias mitigation in models.