Vestiaire Collective - Senior/Staff Machine Learning Engineer

Paris1mo ago

In Office Staff EMEA Cloud Computing Artificial Intelligence Machine Learning Engineer MLOps FastAPI Ray AWS Triton

Requirements

• Experience: 5-8+ years of hands-on experience in Machine Learning Engineering, specifically focused on building and scaling MLOps infrastructure and productionizing ML systems. • Production Infrastructure: Proven expertise in deploying low-latency, high-throughput ML inference services (using FastAPI, TorchServe, Triton Inference Server, or Ray Serve) across both classical lightweight and heavy-width ML models (PyTorch/TensorFlow). Strong preference for AWS (EKS, EC2, SageMaker) / Snowflake and Open Source ecosystems over GCP/Azure. • MLOps & Pipelines: Deep experience building automated, continuous model retraining pipelines to handle concept drift (ranging from daily to weekly cycles). You have orchestrated decoupled, multi-model AI architectures using tools like Airflow, Kubeflow, or Metaflow, and possess strong expertise in model registry and tracking tools like MLflow or Weights & Biases. • Feature Stores: Hands-on experience evaluating, building, or extensively leveraging online (Redis, DynamoDB) and offline (Snowflake, S3) Feature Stores in a production environment. Familiarity with frameworks like Feast or custom dbt-based pipelines is highly valued. • Strategic Builder Mindset: You are an analytical builder who thinks long-term. You can successfully evaluate TCO for bespoke internal systems versus enterprise tools, anticipate technical liabilities, and design robust architectures that handle unpredictable peak traffic surges. • Collaboration & Engineering Hygiene: Strong cross-functional communication skills. You excel at translating complex ML prototypes into highly scalable production code backed by strict version control, rigorous testing, and CI/CD best practices, seamlessly connecting data science innovation with backend engineering execution. • Relevant Domain Expertise: Background in E-commerce, Single-SKU Marketplaces, Search & Recommendation, Trust & Safety, or Counterfeit Detection. • Vision, Edge & Optimization: Hands-on experience with Vector Databases, Visual RAG pipelines, deploying Deep Learning VLM models, and optimizing models for edge computing or low-latency inference (e.g., ONNX, TensorRT). • Infrastructure & Observability: Advanced experience with containerization (Docker, Kubernetes), Infrastructure as Code (Terraform), and data transformation workflows (dbt). Familiarity with setting up advanced monitoring for model performance, concept drift, and system health (Datadog, Prometheus).

Responsibilities

• 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 models focused on fraud detection and luxury product authentication, immediately improving our trust and safety ecosystem. • Mid-Term Foundation (MLOps Lifecycle & Infrastructure): Lead the end-to-end foundational groundwork of our ML lifecycle by designing robust systems for Data & Feature Management, Model Tracking & Registry, and Model Serving & Monitoring. You will scale infrastructure by automating continuous retraining pipelines that handle diverse deployment cadences (from daily fraud detection to weekly recommendations), design resilient multi-model architectures, and critically evaluate the technical overhead and TCO of our in-house tools against enterprise-grade platforms to ensure long-term resilience. • Long-Term Vision (Centralizing 360-Degree MLE Capabilities): Act as a pioneer and cornerstone hire for the ML engineering discipline at Vestiaire Collective, setting the technical standards to help scale the AI/ML organization. You will transition into a centralized foundational role, moving beyond single-squad operations to mentor the team and provide horizontal ML infrastructure support to multiple domains, including Search, Discovery, Pricing, Marketing, and Data Platforms.

Benefits

• Purpose-driven work at scale • High-impact scope & ownership • Work on products used globally, where your decisions have immediate, measurable impact on millions of users across 70+ countries. • A truly international environment • Collaborate with a diverse team of 50+ nationalities across Paris, London, Berlin, New York, Singapore, and Ho Chi Minh City. • Career acceleration in a fast-moving scale-up • Take ownership early, grow fast, and shape your path, as an expert or a future leader. • Learning & growth as a priority • Dedicated budget, continuous feedback culture, and opportunities to work on cutting-edge topics (AI, marketplace dynamics, scalability, etc.). • Flexible ways of working • Hybrid model (typically 2 days remote per week), with trust and autonomy at the core of how we operate. • Give back through action • Including bonus, health coverage, lunch vouchers, Gym-Pass, and additional legal perks depending on your location. • Research shows that candidates from underrepresented backgrounds including women, people with disabilities, and other marginalized communities, are less likely to apply unless they meet 100% of the criteria. • At Vestiaire Collective, we believe diversity drives better decisions, stronger products, and more meaningful impact.