DE&A - AIML - Machine Learning - Python
Zensar Technologies
Salary not disclosed
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Description
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
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.
About this role
Zensar is looking for an AI/ML engineer to build the bridge between data science models and business-ready solutions. You'd own the full pipeline from prescriptive optimization engines through generative AI components, translating raw model outputs into actionable recommendations, automated reports, and plain-language narratives that business teams can actually use. This means working with mathematical programming tools, LLM frameworks, and Python to create end-to-end systems that combine optimization logic with generative AI for explainability and impact.
The role demands 3–5 years of applied AI or software engineering experience, with solid grounding in both optimization (PuLP, OR-Tools, linear programming) and modern LLM work (prompt engineering, LangChain, Hugging Face, API deployment). You'll need strong Python fundamentals and a track record building automated data pipelines and reporting systems. Supply chain or inventory optimization background is a plus but not required. This is an in-office position at Zensar's India location, suited for someone who wants to move beyond model development into production systems that drive real business value.
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Pay for this role
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