Senior Data Science/ML Engineer - Financial Crime

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 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. Who You Are Must-Haves: 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. Nice-to-Haves: 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).

Artefact, a global AI and data consulting company with rapid growth, is looking for a creative and tech-savvy Senior AI Engineer (m/f/d) to join the tech team full-time. Ideally, you are located in Hamburg, Munich, Berlin or nearby - but if you're based elsewhere in Germany and a great fit, we would still love to hear from you. Could this be you? Our data & AI experts develop production-ready, scalable solutions that bring real business value to our clients. You’ll work in interdisciplinary teams of data scientists, engineers, analysts and consultants to shape the future of data- and AI-driven products.   Your responsibilities: Innovate. You’ll help identify business needs, explore data and AI use cases, and drive projects from idea to production - whether it’s a proof-of-concept or a scalable solution. Build. You’ll own your work end-to-end - from concept and architecture to implementation, optimization, and delivery. You design smart, robust solutions using data or LLMs and other AI technologies. Train. You’ll stay ahead of the curve - experimenting with new models, prompt engineering, fine-tuning, and tools. You’ll also share your knowledge within the team and benefit from our partners’ training offers (Google, AWS, etc.). Collaborate. You’ll work closely with clients, product owners, and non-technical stakeholders, balancing technical excellence with practical business impact. Gain broad experience: * Work on 1-3 projects per year across different industries and use cases - from customer service automation to knowledge management and internal tools. * Build real-world data and AI applications using modern tools like LangChain, PydanticAI, MCP servers, RAG pipelines, vector databases (e.g. FAISS, Weaviate), LlamaIndex, Vertex AI, OpenAI APIs, and Hugging Face models. * Shape the way clients use data and AI, driving innovation and best practices in production environments.   Your mindset: * Curious & forward-thinking. You are passionate about solving complex problems using cutting-edge AI and data technologies. * Hands-on. You have experience with LLMs (e.g. OpenAI, Claude, Gemini, LLaMA), prompt engineering, API integration, and ML frameworks. * Holistic. You understand the full ML lifecycle, including data preparation, model deployment, evaluation, and monitoring. * Communicative. You can break down technical concepts for diverse audiences in English and ideally in German as well. * Supportive. You coach junior team members, provide constructive feedback, and actively contribute to our culture of learning.   Profile: * Degree in computer science, AI, data science or similar field. * Experience: 3+ years of experience in machine learning or AI engineering, with hands-on AI projects in production. * Proficiency in Python and cloud-based AI services (GCP, AWS, or Azure). * Solid understanding of data analysis/engineering and AI-specific components like RAG, prompt design, fine-tuning, embeddings, and model evaluation. * Familiar with DevOps and ML-Ops best practices (Docker, Kubernetes, CI/CD). * Strong problem-solving skills, a sense of ownership, and a structured approach to work. * Languages: Business-fluent German and English (both written and spoken) are mandatory to participate in client workshops and deliver polished presentations. * Work Eligibility: A valid work permit for Germany.   Why ARTEFACT? * Challenging projects with national and international clients across industries (e.g. L’Oréal, Samsung, Allianz, Sanofi). * Diverse career paths, promotions based on your performance - not tenure. * Strong team culture and real collaboration across disciplines. * Personal development through workshops, certifications, coaching, and access to partner programs (Google, AWS, etc.). * Attractive benefits: hybrid work, flexible hours, 1 additional day off for your birthday, Christmas & New Year's Eve off, mental health support, 4 weeks of workation, corporate benefits, office brunch, team events, and more.   Let’s shape the future of AI - together! Don't worry if you don't meet all the criteria! At Artefact, we value motivation, pragmatic problem-solving, and potential above all else. If you are excited about shaping the future of AI and ready to make a real impact, we'd love to hear from you. Artefact is a global consulting company specializing in data and AI services, headquartered in Paris. With 2,000+ consultants, data scientists, and engineers across 26 countries, we work with global market leaders. At our German offices, we are on a rapid growth trajectory, advising leading national and international clients cross-industry on how to unlock the full potential of their data, build scalable data architectures, and implement cutting-edge AI solutions. Artefact is dedicated to leveraging data and AI to enhance organizations and their people. We believe that unique perspectives fuel innovation. At Artefact, we are committed to creating an inclusive environment where everyone can thrive. We welcome and consider all applications purely based on merit, skills, and potential - regardless of gender identity, sexual orientation, race, ethnicity, religion, age, background, or disability. Come as you are! Curious to learn more? Reach out to us at: bewerbung-de@artefact.com.