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.
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.
Sr Machine Learning Engineer
At Trafilea, we’re scaling globally loved DTC brands by combining ecommerce excellence with AI-powered innovation. We’re not just building models — we’re deploying production-ready ML systems that process millions of transactions and interactions daily, directly influencing revenue and customer experience.
As a Senior Machine Learning Engineer, you’ll own the full ML lifecycle — from research to production deployment on AWS. You’ll shape our ML architecture and roadmap, collaborate directly with business stakeholders, and solve diverse challenges like recommendation systems, demand forecasting, customer segmentation, and pricing optimization.
What You’ll Do
Design, develop, and deploy production-grade ML models using MLFlow, SageMaker, and containerized workflows.
Own ML projects end-to-end: research, experimentation, deployment, monitoring, and iteration.
Build scalable data pipelines and ensure robust MLOps practices across the stack.
Collaborate with product and business teams to align models with strategic goals and measurable impact.
Work on diverse ecommerce challenges — personalization, demand forecasting, pricing, customer insights.
Maintain balance between experimentation with cutting-edge techniques and ensuring production stability.
Mentor peers and help shape the long-term ML architecture and best practices at Trafilea.
Who You Are
5+ years of ML engineering experience, or a Senior Data Scientist ready to transition into production-focused ML.
Proven track record of deploying ML models into production environments at scale.
Strong engineering background — you go beyond notebooks and write production-ready, tested, maintainable code.
Hands-on experience with Python, SQL, and cloud ML services (AWS preferred).
Familiarity with MLFlow, SageMaker, containerization (Docker/Kubernetes), and CI/CD pipelines.
Business acumen — able to translate technical capabilities into real business value.
Curious, innovative, and comfortable experimenting while maintaining a focus on operational excellence.
Strong communication skills and ability to work effectively in a remote-first, global team
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.
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.
Sr Machine Learning Engineer
At Trafilea, we’re scaling globally loved DTC brands by combining ecommerce excellence with AI-powered innovation. We’re not just building models — we’re deploying production-ready ML systems that process millions of transactions and interactions daily, directly influencing revenue and customer experience.
As a Senior Machine Learning Engineer, you’ll own the full ML lifecycle — from research to production deployment on AWS. You’ll shape our ML architecture and roadmap, collaborate directly with business stakeholders, and solve diverse challenges like recommendation systems, demand forecasting, customer segmentation, and pricing optimization.
What You’ll Do
Design, develop, and deploy production-grade ML models using MLFlow, SageMaker, and containerized workflows.
Own ML projects end-to-end: research, experimentation, deployment, monitoring, and iteration.
Build scalable data pipelines and ensure robust MLOps practices across the stack.
Collaborate with product and business teams to align models with strategic goals and measurable impact.
Work on diverse ecommerce challenges — personalization, demand forecasting, pricing, customer insights.
Maintain balance between experimentation with cutting-edge techniques and ensuring production stability.
Mentor peers and help shape the long-term ML architecture and best practices at Trafilea.
Who You Are
5+ years of ML engineering experience, or a Senior Data Scientist ready to transition into production-focused ML.
Proven track record of deploying ML models into production environments at scale.
Strong engineering background — you go beyond notebooks and write production-ready, tested, maintainable code.
Hands-on experience with Python, SQL, and cloud ML services (AWS preferred).
Familiarity with MLFlow, SageMaker, containerization (Docker/Kubernetes), and CI/CD pipelines.
Business acumen — able to translate technical capabilities into real business value.
Curious, innovative, and comfortable experimenting while maintaining a focus on operational excellence.
Strong communication skills and ability to work effectively in a remote-first, global team