DE&A - AIML - Machine Learning - Python

AI/ML Engineer Role Overview Responsible for building prescriptive and generative AI components that translate model outputs into actionable business recommendations. Bridges the gap between data science outputs and production-ready business deliverables. Experience Required: 3–5 years Key Responsibilities Build prescriptive and optimisation engines using mathematical programming and heuristic solvers Design, develope and implement LLM solutions within secure enterprise infrastructure Engineer LLM prompts to generate plain-language business narratives and ranked recommendations Build automated report generation pipelines delivering structured outputs to business consumers Integrate ML model outputs with generative AI components for consistent and explainable end-to-end delivery Build rule-based trigger engines and exception management workflows Support A/B testing frameworks to compare AI-driven vs. baseline recommendations Design and implement impact analysis and counterfactual simulation capabilities Required Skills 3–5 years of experience in AI/ML engineering, software engineering, or applied AI development Experience with mathematical optimisation ( PuLP , OR-Tools, linear programming) Proficiency in LLM prompt engineering and self-hosted or API-based model deployment Familiarity with LLM frameworks ( LangChain , Hugging Face, OpenAI API) Strong Python skills and experience building automated data and reporting pipelines Knowledge of NLP and generative AI techniques Experience with supply chain or inventory optimisation preferred AI/ML Engineer Role Overview Responsible for building prescriptive and generative AI components that translate model outputs into actionable business recommendations. Bridges the gap between data science outputs and production-ready business deliverables. Experience Required: 3–5 years Key Responsibilities Build prescriptive and optimisation engines using mathematical programming and heuristic solvers Design, develope and implement LLM solutions within secure enterprise infrastructure Engineer LLM prompts to generate plain-language business narratives and ranked recommendations Build automated report generation pipelines delivering structured outputs to business consumers Integrate ML model outputs with generative AI components for consistent and explainable end-to-end delivery Build rule-based trigger engines and exception management workflows Support A/B testing frameworks to compare AI-driven vs. baseline recommendations Design and implement impact analysis and counterfactual simulation capabilities Required Skills 3–5 years of experience in AI/ML engineering, software engineering, or applied AI development Experience with mathematical optimisation ( PuLP , OR-Tools, linear programming) Proficiency in LLM prompt engineering and self-hosted or API-based model deployment Familiarity with LLM frameworks ( LangChain , Hugging Face, OpenAI API) Strong Python skills and experience building automated data and reporting pipelines Knowledge of NLP and generative AI techniques Experience with supply chain or inventory optimisation preferred