Senior ML Engineer: MLOps Architect for Low-Latency AI

Vestiairecollective; Paris; Hybride; EUR 75 000 - 95 000; Plein temps

Avantages offerts par ce poste

Competitive compensation & benefits

Flexible working model

Dedicated training budget

Résumé du poste

Vestiaire Collective is seeking a Foundational Machine Learning Engineer to build MLOps infrastructure from the ground up. You will play a critical role in enhancing AI-driven authentication initiatives and expanding machine learning capabilities across various domains.

This role requires deep expertise in Machine Learning Engineering and MLOps. The ideal candidate will have a track record of deploying low-latency ML models and creating automated retraining pipelines.

Join a diverse team dedicated to reshaping the fashion industry towards sustainability.

Qualifications

• 5-8+ years of hands-on experience in Machine Learning Engineering.
• Expertise in deploying low-latency, high-throughput ML inference services.
• Deep experience in building continuous model retraining pipelines.

Responsabilités

• Partner with Operations and Data Scientists to deploy and scale ML models.
• Lead the groundwork for ML lifecycle systems like Data Management and Model Tracking.
• Mentor team and provide foundational ML infrastructure support across domains.

Connaissances

Machine Learning Engineering

MLOps infrastructure

Production Infrastructure

Low-latency ML inference services

Automated model retraining pipelines

Feature Stores

Cross-functional communication

Formation

Bachelor's or Master's degree in a relevant field

Outils

AWS

Docker

Kubernetes

FastAPI

MLflow

Description du poste

Vestiaire Collective is seeking a Foundational Machine Learning Engineer to build MLOps infrastructure from the ground up. You will play a critical role in enhancing AI-driven authentication initiatives and expanding machine learning capabilities across various domains.

This role requires deep expertise in Machine Learning Engineering and MLOps. The ideal candidate will have a track record of deploying low-latency ML models and creating automated retraining pipelines.

Join a diverse team dedicated to reshaping the fashion industry towards sustainability.