Lago

Open-source API-first metering and billing platform

Senior AI/ML Engineer - Inventory Forecasting & Decision Systems

Applied Machine LearningConfirmed live in the last 24 hours

Full-timeRemote in Brazil$20 - $40 /hr

About the Job

Requirements

The role requires 5+ years of Python experience in production machine-learning systems, beyond notebooks or research.
The role requires deep experience with statistical modeling, including ensemble methods, k-nearest neighbors, calibration, cross-validation, and feature engineering.
The role requires expertise in time-series modeling and forecasting, including seasonality, trend decomposition, safety stock, and demand planning.
The role requires a proven track record of shipping machine-learning models that drive business decisions in forecasting, pricing, or demand planning.
The role requires experience handling messy real-world data, including bias correction, stale-signal handling, error cancellation, and distribution shifts.
The role requires experience with API integration and data-pipeline architecture at scale.
The role requires hands-on experience with large language model and AI-agent workflows, including prompt engineering and evaluation frameworks.
The role requires the ability to validate models rigorously using leave-one-out validation, backtesting, and analysis of production-versus-offline metric gaps.
The role requires self-direction and comfort working in a fast-evolving, small-team environment.

Responsibilities

Build and improve inventory demand forecasting models using machine-learning and statistical methods.
Own machine-learning models end to end, from data collection and feature engineering through training, deployment, monitoring, and 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 and ensure model reliability through rigorous validation and testing.
Implement large language model and AI-agent workflows to translate domain logic into automated processes.
Operate independently in a small team, set priorities, unblock challenges, and communicate tradeoffs clearly.

Desired Qualifications

Experience in Amazon marketplace, e-commerce, or retail analytics.
Familiarity with similarity-based methods, including k-nearest neighbors, embeddings, and vector search.
Experience maintaining long-lived model systems through repeated iteration cycles.
Prior startup or founder-adjacent experience.

Senior AI/ML Engineer - Inventory Forecasting & Decision Systems

Lago · Brazil (Remote) · Full-time · Posted 2026-03-11

Workplace: remote

Department: Dev

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.

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.

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About the Company

Lago

Open-source API-first metering and billing platform

Lago provides an open-source, API-first platform for metering and usage-based billing designed for complex pricing models. It processes high-volume event data to handle real-time metering, subscription management, entitlements, credits, invoicing, and revenue analytics, and integrates with Stripe, CRMs, and ERPs; it is the central billing logic, not a payment processor. Lago differentiates itself with an open-core model (free AGPLv3 self-hosted) plus paid cloud and premium self-hosted deployments, offering transparency and control to reduce vendor lock-in. Its goal is to help AI, SaaS, and API-first businesses monetize complex pricing at scale with a flexible, scalable billing infrastructure.

Company size: 11-50
Company stage: Not listed
Total funding: Not listed
Headquarters: Not listed
Founded: 2024

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