Senior Machine Learning Engineer
About Trafilea
Trafilea is a dynamic and innovative Tech E-commerce Group that operates multiple direct-to-consumer brands in the intimate apparel and beauty sectors, with a focus on using data-driven strategies to scale their businesses. In addition to our products, we have our own online community dedicated to promoting body positivity. As a rapidly growing global player, Trafilea is committed to creating high-quality products and services that enhance the customer experience and drive long-term growth.
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.
Key responsabilities:
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.
Why Trafilea
Weโre a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
๐ We build and scale our own brands.
๐ฆพ We invest in AI and automation like few others in eCom.
๐ We test fast, grow fast, and help you do the same.
๐ค Be part of a dynamic, diverse, and talented global team.
๐ 100% Remote, USD competitive salary, paid time off, and more.
Education: Degree in Computer Science, Mathematics, Statistics, or related field (advanced student accepted, min 3rd year).
Experience:
Machine Learning Engineer: 3+ years.
Semi Sr: 4+ years.
Sr ML Engineer: 5+ years.
Proven track record in scalable ML model deployment.
Technical Skills:
Python, R, SQL.
ML cloud tools (AWS ecosystem, MLFlow).
Deep understanding of ML lifecycle (KDD, Deep Learning, MLOps, pipelines).
Strong testing, refactoring, and code quality practices.
Attributes:
Strong analytical and problem-solving skills.
Excellent communication skills (technical & non-technical).
Business-oriented mindset; aligns ML with strategic priorities.
Proactive, growth-oriented, and collaborative.
Preferred Experience: Marketing, e-commerce, or growth-focused ML applications.
Senior Machine Learning Engineer
About Trafilea
Trafilea is a dynamic and innovative Tech E-commerce Group that operates multiple direct-to-consumer brands in the intimate apparel and beauty sectors, with a focus on using data-driven strategies to scale their businesses. In addition to our products, we have our own online community dedicated to promoting body positivity. As a rapidly growing global player, Trafilea is committed to creating high-quality products and services that enhance the customer experience and drive long-term growth.
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.
Key responsabilities:
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.
Why Trafilea
Weโre a tech-led eCommerce group scaling our own globally loved DTC brands, while helping ambitious talent grow just as fast.
๐ We build and scale our own brands.
๐ฆพ We invest in AI and automation like few others in eCom.
๐ We test fast, grow fast, and help you do the same.
๐ค Be part of a dynamic, diverse, and talented global team.
๐ 100% Remote, USD competitive salary, paid time off, and more.
Education: Degree in Computer Science, Mathematics, Statistics, or related field (advanced student accepted, min 3rd year).
Experience:
Machine Learning Engineer: 3+ years.
Semi Sr: 4+ years.
Sr ML Engineer: 5+ years.
Proven track record in scalable ML model deployment.
Technical Skills:
Python, R, SQL.
ML cloud tools (AWS ecosystem, MLFlow).
Deep understanding of ML lifecycle (KDD, Deep Learning, MLOps, pipelines).
Strong testing, refactoring, and code quality practices.
Attributes:
Strong analytical and problem-solving skills.
Excellent communication skills (technical & non-technical).
Business-oriented mindset; aligns ML with strategic priorities.
Proactive, growth-oriented, and collaborative.
Preferred Experience: Marketing, e-commerce, or growth-focused ML applications.