Senior AI/ML Engineer - Inventory Forecasting & Decision Systems
About the role
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.
What you'll do
- 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
- 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.
About LAGO
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