Role Description You'll play a key role by: - This role sits as part of a multidisciplinary squad, collaborating with other Machine Learning Scientists, Data Scientists, Backend Engineers, Operations specialists, Product managers, and Risk managers. - Leveraging your deep experience of developing and deploying advanced Machine Learning models to: - Automatically and accurately detect suspicious user behaviours while minimising impact to genuine customers and operational costs. - Adapt quickly and appropriately to changing fraud and financial crime trends, ensuring our detection systems remain performant through time. - Design machine learning solutions that scale globally. - The technical approaches you take to solve these problems will be very much in your hands and we’ll strongly encourage and support experimentation and innovation. - Justifying and demonstrating effectiveness along the way, ensuring the approach meets our business and customer needs. Qualifications - What we’re doing here at Monzo excites you! - You have a track record of deploying advanced Machine Learning models tackling real business problems with demonstrable impact, preferably in a fast moving tech company. - You're impact driven and excited to own the end to end journey that starts with a business problem and ends with your solution having a measurable impact in production. - You have a passion for sharing knowledge and raising the technical bar across the team. - You have a self-starter mindset; you proactively identify the most impactful issues and opportunities and collaboratively tackle them without being told to do so. - Using advanced ML techniques to ensure Monzo’s customers money stays safe, even if their card, phone or account is compromised, sounds exciting to you. - You have extensive experience writing production Python code and a strong command of SQL. - You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices. - You have experience developing and shipping deep learning, graph-based, and/or sequence-based ML architectures to production and delivering business impact. - You thrive working on ambiguous problems and have a track record of helping your team and stakeholders resolve that ambiguity. - You have strong communication skills and are able to explain complex technical concepts to non-technical stakeholders. - You want to be involved in building a product that you and the people you know use every day, with a product mindset that prioritises customer outcomes and data-informed decisions. - You're excited about fast-moving developments in Machine Learning and can communicate those ideas to colleagues who are not familiar with the domain. - You’re adaptable, curious and enjoy learning new technologies and ideas. Requirements - Experience in supporting your team in shaping the ML strategy of your area. - Experience working with financial crime, operations and in regulated institutions. - Commercial experience writing critical production code and working with microservices. - Experience in evaluating ML models in live environments such as through A/B tests. Benefits - We’ll help you relocate to the UK. - We can sponsor your visa. - This role can be based in our London office, but we're open to distributed working within the UK (with ad hoc meetings in London). - We offer flexible working hours and trust you to work enough hours to do your job well, and at times that suit you and your team. - £1,000 learning budget each year to use on books, training courses and conferences. - We will set you up to work from home; all employees are given Macbooks and for fully remote workers we will provide extra support for your work-from-home setup. - Plus lots more!

• Design, develop, and deploy production-ready machine learning models with a strong focus on computer vision applications. • Build AI capabilities that identify, track, and analyse construction progress from visual data. • Research, prototype, and implement solutions using LLMs, multimodal AI models, and generative AI technologies. • Evaluate when to leverage commercial foundation models versus developing custom machine learning solutions. • Design, build, and maintain scalable ML pipelines covering data collection, labelling, training, evaluation, deployment, and monitoring. • Source, clean, curate, and prepare high-quality datasets for model training. • Develop and maintain MLOps infrastructure, including model versioning, CI/CD pipelines, deployment automation, and monitoring. • Collaborate with Software Engineers, Product Managers, and AI specialists to integrate machine learning capabilities into production applications. • Optimise model accuracy, inference performance, scalability, and reliability. • Stay current with emerging machine learning techniques, AI frameworks, and industry best practices.

Role Description Wir suchen aktuell: Remote (Senior) Consultant (m/w/d) Machine Learning & AI (SAP / Microsoft / Databricks) in Gescher. DEINE AUFGABEN: - Gemeinsam mit deinen KollegInnen analysierst du fachliche und technische Anforderungen unserer Kunden und entwickelst innovative Lösungen im Bereich Machine Learning und Artificial Intelligence – insbesondere mit Produkten und Services aus dem SAP- und Microsoft-Technologiestack (z. B. SAP Analytics Cloud, SAP Datasphere, Azure Machine Learning, Azure AI Foundry, SAP Databricks, Azure Databricks). - Als Senior Consultant übernimmst du zusätzlich Verantwortung für Projekte und Teams – von der konzeptionellen Ausarbeitung über Aufwandsschätzungen bis zur erfolgreichen Umsetzung. - Du stellst sicher, dass Projekte im geplanten Zeitraum umgesetzt werden, erkennst Projektrisiken frühzeitig und führst das Team sicher durch alle Phasen bis zum Go-Live. - Du begleitest die Übergabe in den Echtbetrieb und bist interner wie externer Ansprechpartner für Machine-Learning-, Generative AI- oder Agentic-AI-Themen. - Durch Workshops, Vorträge und Technologie-Events teilst du dein Wissen und treibst den Aufbau unserer AI-Community aktiv voran. Qualifications - Du hast mehrjährige Erfahrung in Data & Analytics-Projekten – idealerweise mit Fokus auf Machine Learning, Generative AI oder Agentic AI. - Du beherrscht sowohl Python als auch SQL. - Erfahrungen von relevanten ML-Frameworks (z. B. scikit-learn, TensorFlow, MLFlow) oder Generative AI- & Agentic-AI-Frameworks (z. B. LangChain, LlamaIndex, Microsoft Autogen) sind von Vorteil. - Du arbeitest gerne konzeptionell und lösungsorientiert, bringst Eigeninitiative und Kommunikationsstärke mit und kannst komplexe Themen verständlich vermitteln. - Verhandlungssichere (C-Niveau) Deutsch- und sehr gute Englischkenntnisse sind für dich selbstverständlich. - Für die Senior-Position bringst du Erfahrung in der Projektleitung und im Kundenmanagement mit. Benefits - Wir stellen standortunabhängig ein. Du kannst zu 90 % von zuhause aus oder an einem unserer Standorte arbeiten, wenn dieser für dich gut erreichbar ist. Zu gelegentlichen Kundenterminen und Teamevents startest du von deinem Lebensmittelpunkt aus, egal wo in Deutschland du wohnst. - 130 Data & Analytics Consultants zum Austausch sowie eine interne Weiterbildungsacademy. - Langfristige Projekte mit wechselnden technologischen Herausforderungen. - Ein festes Budget für Weiterbildungsmöglichkeiten sowie persönliche und fachliche Entwicklungsperspektiven. - Eine gute Work-Life-Balance durch flexible Arbeitszeiten, Überstundenausgleich sowie bis zu 40 Tagen Urlaub. - Sowohl erstklassige Hard- und Softwareausstattung als auch Leasingangebote für Firmenwagen, IT-Hardware und Fahrräder. - Kurze Wege im Unternehmen, ein fairer Umgang miteinander sowie unterhaltsame Teamevents. Contact and Application Bewirb dich schnell und einfach direkt hier. Ergreife die Initiative und sprich mit uns über deine Karriereziele. Deine Ansprechpartnerin: Frau Julia Beer Recruiting | Personalmarketing Kontakt: Windhoff Group Am Campus 17, 48712 Gescher +49 (0) 25 42 / 95 59 18 j.beer@windhoff-group.de

• Operate across the full ML lifecycle (problem framing, data, modeling, evaluation, deployment, monitoring, and oncall), designing scalable ML pipelines and championing responsible AI (bias, safety, explainability) for ACU’s models and signals in production. • Provide technical leadership and mentorship to MLEs and SWEs doing ML work in ACU, design reviews, setting technical standards, and uplifting the team’s modeling and systems craft. • Develop evaluation systems and quality monitoring systems for content understanding signals, using SOTA LM-judge practices. • Drive operational excellence for ACU’s ML systems by defining SLOs, alerting, and dashboards for key signals (coverage, latency, precision/recall, cost) • Build and evolve content understanding capabilities for commercial conversations (e.g., reviews vs. recommendations vs. comparisons vs. Q&A; sentiment and stance; product entities and categories) and operationalize them as robust signals that power contextual and shopping ads, auto-targeting, new formats, and insights products. • Drive LLM and modern ML best practices within ACU: define when to prompt, finetune, or distill; design evaluation and safety harnesses; and lead at least one major distillation effort to replace external APIs with in-house models.