AI/ML/Gen AI Engineer

Job description

Job Responsibilities - Build and maintain mathematical optimization models — objective functions, constraints, and penalty calibration - Encode and validate business rules, contract parameters, and operational constraints into model inputs - Execute regression testing and model health checks before and after every production run - Conduct scenario and sensitivity analysis with documented trade-offs and business recommendations - Validate all input files pre-run — NULL checks, format errors, anomalies, and data readiness sign-off - Monitor data pipeline health, audit logs, and ingestion failures across recurring run cycles - Perform data quality assessments — missingness, outliers, duplicate records, and consistency checks - Validate model outputs and savings calculations — ensuring mathematical accuracy and business defensibility - Review compliance and performance tracking — compare actuals vs recommendations and document deviations - Review output files for anomalies and formatting issues before stakeholder delivery - Support recurring run preparation — scenario setup, input file review, and run orchestration - Triage platform issues — classify severity, gather diagnostics, and escalate with clear context - Monitor cloud pipeline health — ingestion, compute, and delivery layer checks - Maintain run logs, SOPs, runbooks, and knowledge base in structured auditable format - Partner with business stakeholders to explain model outputs and recommendations in plain language - Mentor junior team members on best practices, coding standards, and documentation discipline **Required Skills** - 3–8+ years experience in Data Science / Operations Research. - Hands-on experience with optimization solvers — CPLEX and OR-Tools.(Operation Research Tools) - Python — modeling, data validation, automation scripting, production-quality coding - SQL — data querying, pipeline monitoring, audit log review - Cloud platform experience — AWS or equivalent - Strong documentation and stakeholder communication skills **Preferred Skills** - Pipeline orchestration tools — Dataiku, Airflow, or equivalent - Containerization — Docker and Kubernetes - REST API development — FastAPI or equivalent - Open-source solver experience — PuLP, OR-Tools - Domain knowledge in logistics, supply chain, or network optimization - Cloud certification — AWS