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Senior AI/ML Engineer - Inventory Forecasting & Decision Systems at Lago. Role: Senior AI/ML Engineer — Inventory Forecasting & Decision Systems. Hours: 9am - 6pm Eastern Time (Remote). USD Salary: $20-$40/HR. We are seeking a highly skilled Senior AI/ML Engineer to drive the development of advanced inventory forecasting and decision systems. This is a senior, individual-contributor role with direct business impact, ideal for a self-directed engineer comfortable navigating ambiguity and building end-to-end ML solutions.. Responsibilities. Build and improve . inventory demand forecasting models. using ML and statistical methods. . Own ML models . end-to-end. : data collection → feature engineering → training → deployment → monitoring → iteration. . Develop . decision systems. that support inventory planning, pricing, and demand decisions. . Build and maintain . data pipelines. and API integrations for external and internal data sources. . Work with . messy real-world data. to ensure model reliability through rigorous validation and testing. . Implement . LLM/AI-agent workflows. to translate domain logic into automated processes. . Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly. . Must-Have Qualifications. 5+ years of Python experience in . production ML systems. (beyond notebooks/research). . Deep experience with . statistical modeling. , including ensemble methods, kNN, calibration, cross-validation, and feature engineering. . Expertise in . time-series modeling & forecasting. , including seasonality, trend decomposition, safety stock, and demand planning. . Proven track record of shipping ML models that . drive real business decisions. (forecasting, pricing, demand planning). . Strong intuition for . messy, real-world data. , including bias correction, stale signal handling, error cancellation, and distribution shifts. . Experience with . API integration and data pipeline architecture. at scale. . Hands-on experience with . LLM/AI-agent workflows. , including prompt engineering and evaluation frameworks. . Proven ability to . validate models rigorously. : LOO, backtesting, production vs offline metric gaps. . Self-directed, comfortable in a . fast-evolving, small team environment. . . Nice-to-Have Qualifications. Experience in . Amazon marketplace, e-commerce, or retail analytics. . . Familiarity with . similarity-based methods. (kNN, embeddings, vector search). . Experience maintaining . long-lived model systems. (v1 → v30+ iteration cycles). . Prior . startup or founder-adjacent experience. . . Company Location: Romania.