Senior AI/ML Engineer - Inventory Forecasting & Decision Systems
Lago Open · verified Oct 22, 2026 At a glance
Senior Machine Learning Engineering role at Lago. Remote, Philippines · full-time.
Pay not stated Machine Learning Engineering salary
aimlroles summary, based on the employer's posting.
What you'll do
- Improve inventory demand forecasts by applying machine-learning and statistical approaches
- Carry models through data gathering, feature development, training, release, monitoring and successive refinement
- Create decision systems for inventory plans, pricing choices and demand decisions
- Build data pipelines and API connections for internal and external sources, checking models against messy inputs
- Automate domain rules through workflows built with LLMs or AI agents
What you bring
- At least five years using Python for production ML systems, rather than notebooks or research alone
- Deep statistical and time-series modeling expertise, including forecasting, seasonal patterns, safety stock and demand planning
- A track record of shipping ML models that shape business decisions and validating them through backtesting or production metrics
- Hands-on background with data pipeline architecture, API integration and LLM or AI-agent workflows
Who this fits
This is a senior individual-contributor position for someone who can set priorities independently, handle ambiguity and communicate tradeoffs. The role is remote in the Philippines, with hours from 9am to 6pm Eastern Time. Recruitment requires candidates to review and accept Lago’s confidentiality and non-circumvention terms.
From the employer
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.