Senior AI/ML Engineer - Inventory Forecasting & Decision Systems
Salary$42k – $83k
LocationPhilippines
Work moderemote
Typefull-time
DepartmentDev
Company size1+ people
First seen1w ago
Last seen3d ago
About the role
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
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Build and improve inventory demand forecasting models using ML and statistical methods.
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Own ML models end-to-end: data collection → feature engineering → training → deployment → monitoring → iteration.
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Develop decision systems that support inventory planning, pricing, and demand decisions.
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Build and maintain data pipelines and API integrations for external and internal data sources.
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Work with messy real-world data to ensure model reliability through rigorous validation and testing.
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Implement LLM/AI-agent workflows to translate domain logic into automated processes.
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Operate independently in a small team, setting priorities, unblocking challenges, and communicating tradeoffs clearly.
Requirements
Must-Have Qualifications
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5+ years of Python experience in production ML systems (beyond notebooks/research).
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Deep experience with statistical modeling, including ensemble methods, kNN, calibration, cross-validation, and feature engineering.
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Expertise in time-series modeling & forecasting, including seasonality, trend decomposition, safety stock, and demand planning.
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Proven track record of shipping ML models that drive real business decisions (forecasting, pricing, demand planning).
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Strong intuition for messy, real-world data, including bias correction, stale signal handling, error cancellation, and distribution shifts.
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Experience with API integration and data pipeline architecture at scale.
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Hands-on experience with LLM/AI-agent workflows, including prompt engineering and evaluation frameworks.
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Proven ability to validate models rigorously: LOO, backtesting, production vs offline metric gaps.
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Self-directed, comfortable in a fast-evolving, small team environment.
Nice-to-Have Qualifications
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Experience in Amazon marketplace, e-commerce, or retail analytics.
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Familiarity with similarity-based methods (kNN, embeddings, vector search).
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Experience maintaining long-lived model systems (v1 → v30+ iteration cycles).
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Prior startup or founder-adjacent experience.
Benefits
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Remote Work: Work from anywhere—our team is global, and we value work-life balance.
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Growth Opportunities: As a key player i you’ll have the chance to shape your role and grow with us.
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Innovative Culture: Join a team that is passionate about leveraging data to solve challenges and drive success in a rapidly evolving market.
Legal
As part of our recruitment process, all candidates are kindly asked to read, understand, and agree toLago’s Confidentiality and Non-Circumvention Agreement. This ensures a respectful and professional experience for everyone involved.