Senior AI & ML Engineer – AML Search Quality

SEON

. Drive modeling and experimentation for SEON's fuzzy matching and AML screening quality .

Posted 10/30/2026full-timeRemote • HungarySenior💰 HUF 22,860,182 - HUF 30,928,404 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data science and machine learning, with a strong focus on model deployment, monitoring, and evaluation. Proficient in Python, statistical analysis, and NLP techniques, while effectively communicating complex modeling concepts to diverse stakeholders.

Highest-signal resume keywords

Data Science ExperienceMachine Learning Model DeploymentStatistical AnalysisNatural Language ProcessingCloud Computing (AWS)

ATS Keywords

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Hard Skills

PythonStatistical AnalysisExperiment DesignNLPText ClassificationNamed Entity RecognitionSQLData AnalysisModel MonitoringData Pipeline Deployment

Soft Skills

Clear CommunicationProblem-SolvingMentoringCollaborationRisk Management

Tools & Technologies

ElasticsearchAI-Assisted Development ToolsAPIsCloud Services

Industry Keywords

AMLKYCFinancial ServicesData DriftBias

Tech Stack

Tools & technologies

AWSCloudElasticSearchPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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