Vestiaire Collective
Fashion Technology
Senior/StaffMachineLearningEngineer
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“Senior/Staff Machine Learning Engineer at Vestiaire Collective. Skills: Machine Learning, MLOps, Infrastructure, Architecture. Build MLOps infrastructure. Drive AI authentication initiatives”
What You'll Achieve.
Improve trust and safety; Deliver high-throughput impact; Deliver low-latency impact
Industry & Context.
Analytical builder; Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
5-8+ years Machine Learning Engineering, Build and scale MLOps infrastructure, Productionize ML systems, Deploy low-latency, high-throughput ML inference services, Deploy classical lightweight ML models, Deploy heavy-width ML models, Automate continuous model retraining pipelines, Handle concept drift, Orchestrate decoupled, multi-model AI architectures, Evaluate TCO for internal systems, Anticipate technical liabilities, Design robust architectures, Handle unpredictable peak traffic surges, Cross-functional communication skills, Translate ML prototypes to production code, Strict version control, Rigorous testing, CI/CD best practices, Connect data science to backend engineering
Nice to Have
E-commerce domain expertise, Single-SKU Marketplaces domain expertise, Search & Recommendation domain expertise, Trust & Safety domain expertise, Counterfeit Detection domain expertise, Vector Databases experience, Visual RAG pipelines experience, Deep Learning VLM models experience, Optimize models for edge computing, Optimize models for low-latency inference, Advanced containerization experience, Advanced Infrastructure as Code experience, Advanced data transformation workflows experience, Set up advanced monitoring, Monitor model performance, Monitor concept drift, Monitor system health
What You'll Do.
Build MLOps infrastructure
Drive AI authentication initiatives
Deploy multi-model approaches
Deploy computer vision models
Detect counterfeit products
Scale foundational architecture
Expand ML capabilities
Power broader domains
Focus on search systems
Focus on recommendation systems
Expand into dynamic pricing
Expand into marketing technologies
Design robust architectures
Design decoupled architectures
Spearhead MLOps strategy
Prioritize system maintainability
Prioritize engineering hygiene
Ensure reliable deployment
Deliver high-throughput business impact
Deliver low-latency business impact
Partner with Operations squads
Partner with Data Scientists
Accelerate ML prototypes
Accelerate RAG prototypes
Improve trust and safety
Lead ML lifecycle groundwork
Design Data Management systems
Design Feature Management systems
Design Model Tracking systems
Design Model Registry systems
Design Model Serving systems
Design Model Monitoring systems
Automate retraining pipelines
Handle diverse deployment cadences
Design resilient architectures
Evaluate technical overhead
Set technical standards
Scale AI/ML organization
Provide horizontal ML infrastructure support
How You'll Work.
Team & Collaboration
Cross-functional communication; Operations squads; Data Scientists; Data Platform; Backend Engineering; Director of Data
Communication Scope
Cross-functional communication
Process & Methodology
Roadmap planning, Agile
Full Job Description
## Description Vestiaire Collective is the leading global online marketplace for desirable pre-loved fashion. Our mission is to transform the fashion industry for a more sustainable future by empowering our community to promote the circular fashion movement. Vestiaire was founded in 2009 and is headquartered in Paris with offices in London, Berlin, New York, Singapore, Ho Chi Minh, and warehouses in Tourcoing (France), Crawley (UK), Hong Kong and New York. We currently have a diverse global team of 600 employees representing more than 50 nationalities. Our values are Activism, Transparency, Dedication and Greatness and Collective. About the Role We are seeking a Foundational Machine Learning Engineer for a high-impact greenfield opportunity to build our MLOps infrastructure from the ground up at Vestiaire Collective. While driving our AI authentication initiatives (deploying multi-model approaches including computer vision for luxury product authentication and counterfeit detection) will be your immediate focus, your long-term mission will be to scale foundational architecture across the entire marketplace. You will expand our ML capabilities to power broader domains, primarily focusing on search and recommendation systems, with future expansions into dynamic pricing and marketing technologies. Acting as the bridge among Applied Science, Data Platform, and Backend Engineering, you will design robust, decoupled architectures and spearhead the MLOps strategy with our Director of Data, prioritizing system maintainability, engineering hygiene, and the reliable deployment of complex models, ensuring all our ML models across the board deliver high-throughput, low-latency business impact. What You Will Do Short-Term Impact (First 6 Months): Partner closely with the Operations squads and Data Scientists to accelerate ML and RAG prototypes into resilient, production-ready code. You will directly integrate with the team to deploy, optimize, and scale heavy-width CV and VLM mo
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