Senior Machine Learning Engineer
About Trafilea
Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.
With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.
We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.
Why Trafilea
We’re a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
🚀 We build and scale our own brands.
🦾 We invest in AI and automation like few others in eCom.
📈 We test fast, grow fast, and help you do the same.
🤝 Be part of a dynamic, diverse, and talented global team.
🌍 100% Remote, USD competitive salary, paid time off, and more.
Key responsibilities
The mission of the Machine Learning Engineer is to develop, deploy, and maintain advanced machine learning models that drive innovation, efficiency, and business performance across Trafilea. This role bridges business strategy and technical execution by crafting production-ready code, building scalable systems, and applying scientific methodologies to solve complex challenges. The engineer ensures ML initiatives deliver measurable business value and position Trafilea at the forefront of AI-powered growth.
Model Development & Deployment
Build robust, scalable ML models aligned with service architecture.
Write testable, production-ready code with coverage for edge cases and errors.
Integrate models into business systems, ensuring reliability and explainability.
Experimentation & Research
Apply the scientific method and KDD process to model development.
Explore new ML techniques (Deep Learning, Shap values, forecasting methods).
Contribute innovative solutions to high-impact business problems.
Data Engineering & Pipelines
Design scalable data pipelines supporting model features.
Ensure data integrity, reproducibility, and automation in ML workflows.
Business Alignment & Collaboration
Align ML initiatives with strategic goals, contributing to business discussions.
Partner with marketing, growth, and BI teams to optimize performance and decision-making.
Team Development
Mentor peers, contribute to knowledge sharing, and improve team processes.
Provide constructive feedback to colleagues and stakeholders.