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Senior Machine Learning Engineer

Stelle nicht auf LinkedIn

🕒 vor 2 Monaten

🇬🇧 Vereinigtes Königreich – Remote

⏰ Vollzeit

🟠 Senior

🤖 Machine-Learning-Entwickler

🗣️🇺🇸🇬🇧 Englisch erforderlich

Woher diese Stelle stammt

Veröffentlicht auf der Karriereseite von Ravelin Technology, nicht über eine Jobbörse

Von Remote Rocketship zum ersten Mal gesehen vor 2 Monaten

Noch offen auf der Website von Ravelin Technology. Geprüft vor 8 Stunden.

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Ravelin Technology

51 - 200 Mitarbeiter

Gegründet 2014

☁️ SaaS

💳 Fintech

🔐 Sicherheit

💰 €20.650.880 Series C - Ravelin im 2020-07

SaaS • Fintech • Security

Ravelin Technology ist ein B2B-Unternehmen, das Betrugserkennungs- und Präventionslösungen für Online-Zahlungen und digitale Marktplätze anbietet. Mit KI-gesteuerten Modellen und agentengestützter Technik adressiert es Zahlungsbetrug, Rückerstattungs- und Gutscheinmissbrauch, Kontoübernahmen (ATO), 3D Secure-Optimierung, Partnerbetrug auf Marktplätzen und Transaktionsoptimierung. Das Unternehmen bietet APIs, SDKs und Integrationen, sodass Unternehmen seine Echtzeit-Entscheidungs- und Risikoanalysefähigkeiten in ihre Zahlungs- und Kontosicherheits-Workflows einbinden können.

Beschreibung

• Set the technical direction bridging data science and engineering. • Own the architecture, scalability, and reliability of high-performance machine learning systems for the fraud detection platform. • Optimize multi-GPU training for foundational payments models such as Transformers. • Define how data is modeled, stored, and served, influencing feature generation pipelines and data quality across the ML lifecycle. • Take strategic ownership of ML infrastructure, platforms, and tools supporting Data Science experimentation. • Collaborate with engineers and data scientists to operate and optimize machine learning at scale. • Lead the design, architecture, and orchestration of end-to-end ML pipelines from raw data extraction and feature engineering through training and inference. • Develop high-throughput pipelines for terabyte-scale datasets and multi-GPU training. • Drive cross-functional initiatives with Data Engineering, Infra, and other teams. • Evolve MLOps infrastructure for model versioning, automated deployments, monitoring, and observability. • Mentor team members through code reviews, design discussions, and knowledge sharing. • Improve internal tools and engineering best practices.

🎯 Anforderungen

• Demonstrable experience designing, building, and deploying complex machine learning systems in production. • Deep understanding of the full machine learning lifecycle. • Track record leading design and implementation of scalable training pipelines for large datasets. • Experience with PyTorch or TensorFlow, distributed/multi-GPU training, and transformer architectures. • Familiarity with workflow orchestration tools such as Prefect, Kubeflow, or Argo. • Experience leading complex cross-functional projects and influencing technical direction across teams. • Software engineering fundamentals, including data structures, design patterns, Git, CI/CD, testing, and monitoring. • Exceptional problem-solving skills and ability to lead technical deep-dives through ambiguity. • Collaborative mindset and strong communication skills. • Nice to have: proficiency in Go, C++, Java, or Rust. • Nice to have: familiarity with dbt. • Must pass pre-employment checks and satisfy right-to-work requirements.

🏖️ Vorteile

• Flexible Working Hours & Remote-First Environment — Work when and where you’re most productive, with flexibility and support. • Comprehensive BUPA Health Insurance • £1,000 Annual Wellness and Learning Budget • Monthly Wellbeing and Learning Day — Take every last Friday of the month off • 25 Days Holiday + Bank Holidays + 1 Extra Cultural Day • Mental Health Support via Spill • Aviva Pension Scheme • Ravelin Gives Back — Monthly charitable donations and volunteer opportunities • Fortnightly Randomised Team Lunches • Cycle-to-Work Scheme • BorrowMyDoggy Access • Weekly Board Game Nights & Social Budget • Pre-employment checks including unspent criminal convictions, employment verification, and right to work

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