Senior AI & ML Engineer – AML Search Quality

🔥 0 minutes ago

🇭🇺 Hungary – Remote

💵 Ft22.9M - Ft30.9M / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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SEON

WebsiteLinkedInAll Job Openings

201 - 500 employees

☁️ SaaS

🔐 Security

📋 Compliance

💰 $80M Series C - SEON on 2025-09

SaaS • Security • Compliance

SEON is an AI-driven fraud prevention and AML compliance platform that provides a unified, SaaS-based command center for detecting and preventing payment fraud, account takeover, synthetic identity and other financial crime. The company enriches identity, device and digital-footprint signals (900+ real-time signals) and combines rules-based and machine-learning risk scoring with identity verification, transaction monitoring, case management and automated regulatory reporting. SEON targets businesses such as fintechs, payments providers, iGaming and retail that need real-time fraud screening, KYC/AML workflows and scalable integrations via APIs.

📋 Description

• Drive modeling and experimentation for SEON's fuzzy matching and AML screening quality • Turn ambiguous problems into well-defined approaches and carry them from experiment through release and operation • Build evaluation datasets and metrics using offline and online signals • Design scoring and machine-learning approaches for real-time decisioning, balancing match quality, performance, cost, and operational overhead • Own production quality of models and configurations, including monitoring for data and concept drift, on-call participation, and incident follow-up • Investigate customer-reported matching issues with Product and Customer Success • Collaborate with Product, QA, Architects, DevOps, and Customer Success • Capture experiment learnings for reuse • Introduce AI tools and techniques where they provide clear value • Mentor teammates and raise data science practice across the team

🎯 Requirements

• 5+ years of experience in data science or machine learning, delivering models to production • Strong Python skills • Strong command of statistical analysis and experiment design, including offline and online evaluation of search or matching quality • Experience with NLP or text-based machine learning, such as text classification, named entity recognition (NER), or text matching • Experience owning the full lifecycle of data-driven systems, from data and experimentation to deployment and monitoring • Ability to anticipate data drift, leakage, and bias • Solid background in data analysis and SQL • Working understanding of backend services and APIs • Experience with non-relational or search databases, ideally Elasticsearch • Working experience with a major cloud provider, ideally AWS • Experience deploying models and data pipelines on a major cloud provider • Clear communication of modeling trade-offs to Product and non-technical stakeholders • Track record of turning ambiguous problems into end-to-end solutions • Ability to spot delivery risks early and raise them with a proposed mitigation • Prior experience in AML, KYC, or another regulated financial services domain is an advantage • Experience driving cross-team technical work is an advantage • Experience using AI-assisted development tools is an advantage

🏖️ Benefits

• Remote work within the EU • Additional benefits are shared as part of the job posting • Reasonable adjustments to the recruitment process available upon request

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