Senior ML Infrastructure Engineer

Sumup

About the team: Within the Global Operations organisation, our mission is to build the best customer experience in the fintech industry by delivering an effortless customer experience to all our merchants. We are seeking a skilled and passionate Senior AI / Machine Learning Engineer to join our talented AI team and lead the development of AI models and algorithms that will drive our customer support service to new heights. As a Senior AI / Machine Learning Engineer at SumUp, you will be responsible for building and optimizing state-of-the-art AI models and algorithms. Your expertise with machine learning, deep learning, and LLMs will be crucial in driving the success of our AI-driven initiatives. You will work closely with cross-functional teams, including backend engineers, data scientists and product managers, to translate business requirements into innovative AI solutions. Your contributions will shape the future of our support products and help us stay at the forefront of technological advancements in the field of AI. What you’ll do * Architect, design, develop and deploy our AI solutions and systems in production environments, ensuring reliability, high performance and scalability. * Collaborate and communicate closely with data scientists, product managers, developers and other business stakeholders to bring state-of-the-art AI solutions to Customer Support, enhancing customer experience and improving operational efficiency. * Develop and maintain ML infrastructure and pipelines to support efficient data processing, model training and serving. * Optimize and fine-tune machine learning models to improve accuracy, efficiency and scalability. * Collect, preprocess and clean large text datasets to ensure high-quality input for model training and evaluation. * Embrace software development principles, best practices and industry standards, including version control, CI/CD processes and unit testing frameworks as your day-to-day work. * Collaborate with cross-functional teams to ensure seamless integration of machine learning solutions into software applications and platforms.  You’ll be great for this position if you have: * Bachelor’s degree in Machine Learning, Computer Science or an engineering-related field. * +8 years of proven experience working as a Machine Learning Engineer, focusing on building and deploying scalable machine learning or AI solutions and data-driven systems. * Relevant experience building AI products, such as Chatbot Assistant, RAG system, etc. * Excellent software development engineering skills to design computationally effective solutions and maintenance in large-scale production environments (data version control, model serving, continuous monitoring & alerting) * Experience building and deploying ML models using cloud services (AWS, GCP, or Azure). * Expert in Python and familiarity with MLOps tools (e.g., MLflow, Kubeflow, Airflow, Langfuse). * Experience with machine learning workflow orchestration and algorithms optimisation, feature engineering pipelines, data ingestion and transformation.  * Good understanding of data pipelines, APIs, containers (Docker), and version control (Git). * Excellent analytical and problem-solving skills, with strong attention to detail. * You have working proficiency and communication skills in verbal and written English. Why you should join SumUp: 🌍 Opportunity to work with SumUppers globally on large-scale fintech products used by millions of businesses worldwide, from our Berlin office. This involves an office-first setup. 🌈 Commitment to Diversity and Inclusion: Be part of a workplace that values and promotes diversity, fostering an inclusive environment where everyone's perspectives are respected and embraced 📚 A dedicated annual L&D budget of €2,000 for attending conferences and/or advancing your career through further education. 🚀 Enrolment onto our VSOP program: You will own a stake in SumUp’s future success 💶 A corporate pension scheme where we match up to 20% of your contributions 🔄 30 Days Sabbatical: Enjoy the unique opportunity to take a well-deserved break with our 30 days sabbatical benefit after completing 3 years of employment with SumUp. 🔗 Referral Bonus: Earn additional rewards by referring talented individuals to join the SumUp team. 🚵🏾‍♂️ Numerous other benefits such as Urban Sports Club subsidy, Kita placement assistance, relocation assistance, subsidised office lunches. About us: SumUp is a leading financial technology company, founded in 2012 with the goal of empowering small businesses around the globe. We’re the financial partner of choice for more than 4 million merchants in over 35 markets. We collectively build, plan and fine-tune the technology that drives SumUp and empowers small businesses around the world. We believe in the everyday hero. Those who have the courage to follow their passion and who have the strength and determination to realise their dreams. Small business owners are at the heart of all we do, so we're creating powerful, easy-to-use financial solutions to help them run their business. With a founders mentality and a 'team-first attitude' our diverse teams across Europe, South America, and the United States work together to ensure that small business owners can be successful doing what they love. SumUp is an Equal Employment Opportunity employer that proudly pursues and hires a diverse workforce. SumUp does not make hiring or employment decisions on the basis of race, colour, religion or religious belief, ethnic or national origin, nationality, sex, gender, gender identity, sexual orientation, disability, age or any other basis protected by applicable laws or prohibited by Company policy. SumUp also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Job Application Tip We recognise that candidates feel they need to meet 100% of the job criteria in order to apply for a job. Please note that this is only a guide. If you don’t tick every box, it’s ok too because it means you have room to learn and develop your career at SumUp.

Vestiaire Collective

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).

Peec AI

WHAT YOU’LL DO * Train, test, and ship models that power Peec AI’s recommendations - helping customers boost their visibility in AI search * Develop algorithms that extract actionable insights from AI search behavior, creating data-driven recommendations that help brands increase their AI Search visibility * Own the full model lifecycle from experimentation to production deployment, working closely with engineering to integrate ML solutions into our systems * Design and implement data pipelines to ingest, process, and analyze large volumes of data WHAT WE’RE LOOKING FOR * Proven backend development skills in Python with experience building APIs, data pipelines, or ML infrastructure, and familiarity with tools like FastAPI, Docker, and cloud platforms (preferably GCP) * Deep curiosity about how LLMs work, with the ability to reverse-engineer AI search behavior and translate patterns into actionable product features * Track record of taking projects from research to production in a fast-moving startup environment, with strong problem-solving skills and comfort working with ambiguous, evolving problems * Excellent communication skills with the ability to explain complex technical concepts to customers and stakeholders OUR DATA SCIENCE STACK * Languages: Python, SQL * Libraries: Pandas, NumPy, HuggingFace, PyTorch, TensorFlow, ONNX * Backend: GCP, Cloud Functions, Firestore, Postgres, AlloyDB, BigQuery * AI Models: OpenAI, Claude, Perplexity, Gemini, Llama, etc. BONUS POINTS * Contributions to open-source projects * Deployed side/hobby projects that we can check out * Presented research papers at top ML or AI conferences * Having started a company before or worked at a high-growth startup * Fluency in Typescript WHAT WE OFFER * Exciting and challenging work with real impact and ownership at one of Europe’s fastest-growing Series A startups * Regular team events and off-sites * Aggressive equity compensation package * Paid Dinner & Uber home when working late * The most beautiful office space and work environment in Berlin