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. Requirements 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. Benefits Remote Work: Work from anywhere—our team is global, and we value work-life balance. Growth Opportunities: As a key player i you’ll have the chance to shape your role and grow with us. Innovative Culture: Join a team that is passionate about leveraging data to solve challenges and drive success in a rapidly evolving market. As part of our recruitment process, all candidates are kindly asked to read, understand, and agree to Lago’s Confidentiality and Non-Circumvention Agreement. This ensures a respectful and professional experience for everyone involved.