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

Responsibilities

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

Qualifications

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

At Zensar, we’re “experience-led everything”. We are committed to conceptualizing, designing, engineering, marketing, and managing digital solutions and experiences for over 130 leading enterprises. We are a company driven by a bold purpose: Together, we shape experiences for better futures. Whether for our clients, our people, or the world around us, this belief powers everything we do. At the heart of our culture is ONE with Client - a set of four core values that reflect who we are and how we work: One Zensar, Nurturing, Empowering, and Client Focus.

Part of the $4.8 billion RPG Group, we’re a community of 10,000+ innovators across 30+ global locations, including Milpitas, Seattle, Princeton, Cape Town, London, Zurich, Singapore, and Mexico City. Explore Life at Zensar and join us to Grow. Own. Achieve. Learn. to be the best version of yourself.

We believe the best work happens when individuality is celebrated, growth is encouraged, and well-being is prioritized. We are an equal employment opportunity (EEO) and affirmative action employer, committed to creating an inclusive workplace. All qualified applicants will be considered without regard to race, creed, color, ancestry, religion, sex, national origin, citizenship, age, sexual orientation, gender identity, disability, marital status, family medical leave status, or protected veteran status.