Senior AI/ML Engineer - Inventory Forecasting & Decision Systems
Lago • Mexico
No Relocation
Posted: March 11, 2026
Job Description
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.
Additional Content
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.