Machine Learning Engineer - Inventory Demand Fo...
@ Braintrust

Hybrid
$120,000
Hybrid
Full Time
Posted 21 hours ago

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Job Details

About the Role

The Machine Learning Engineer - Inventory Demand Forecasting role at Braintrust involves building machine learning models for forecasting demand and optimizing inventory systems for an Amazon-focused retail/eCommerce business. The role focuses on creating production-ready models that directly impact purchasing decisions and inventory management.

Project Scope

The role is divided into three monthly phases:

  • Month 1: Build a demand forecasting model, safety stock calculator, and daily stockout alert system.
  • Month 2: Develop a buy box share prediction model, competitor inventory monitoring, and opportunity scanner.
  • Month 3: Create price elasticity models and an automated purchasing decision engine, with full system integration.

Team & Tools

Work with a small existing team including 2 full-time developers and a purchasing team. Access to years of clean historical sales data and existing tools such as PowerBI and internal software is provided. Direct access to decision makers ensures minimal bureaucracy.

Technical & Practical Requirements

  • Experience with inventory/supply chain optimization and production-ready ML models.
  • Amazon, retail, or eCommerce marketplace experience and understanding of competitive dynamics.
  • Ability to build automated decision systems and comprehensive documentation for team integration.
  • A 4-hour test project will be required before full engagement.

Working Arrangement

This is a remote position with CST time zone meetings. The role requires 20-40 hours per week with weekly sync meetings and a strong focus on delivery.

Key skills/competency

  • Machine Learning
  • Forecasting
  • Inventory Optimization
  • Data Analysis
  • Supply Chain
  • eCommerce
  • Automation
  • Retail
  • Documentation
  • Decision Systems

How to Get Hired at Braintrust

🎯 Tips for Getting Hired

  • Customize Resume: Tailor your resume to highlight ML and forecasting skills.
  • Showcase Projects: Include production-ready models and case studies.
  • Research Braintrust: Understand their eCommerce and retail focus.
  • Prepare Test Project: Be ready to demonstrate practical skills.

📝 Interview Preparation Advice

Technical Preparation

Review ML algorithms for time series.
Study inventory optimization methods.
Practice production model deployment.
Analyze historical sales datasets.

Behavioral Questions

Describe handling ambiguous project requirements.
Explain a time you delivered under pressure.
Showcase teamwork in autonomous environments.
Discuss adaptability in fast-paced projects.

Frequently Asked Questions