Senior Machine Learning Engineer

Finom

. Develop full-stack machine learning models, including binary classification and regression, for financial-crime detection and prevention during transaction processing and client onboarding .

Posted 9/24/2026full-timeRemote • RomaniaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and deploying full-stack machine learning models for financial crime detection, with strong skills in SQL, Python, and cloud data platforms. Proficient in model monitoring, infrastructure design, and champion-challenger frameworks to optimize performance in production environments.

Highest-signal resume keywords

Machine Learning EngineeringProduction DeploymentSQLPythonCloud Data Platforms

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Hard Skills

Machine LearningBinary ClassificationRegressionModel MonitoringInfrastructure DesignAPI ServicesChampion-Challenger FrameworkQuantitative AnalysisGraph ModelingFoundation Models

Soft Skills

AnalyticalProactiveResult-DrivenCritical ThinkingSelf-Motivated

Tools & Technologies

FastAPIDatabricks

Industry Keywords

Financial Crime DetectionTransaction ProcessingClient OnboardingDynamic Risk ScoreAlert Suppression

Tech Stack

Tools & technologies

CloudPythonSQL

About the role

Key responsibilities & impact

Develop full-stack machine learning models, including binary classification and regression, for financial-crime detection and prevention during transaction processing and client onboarding
Gather requirements, prototype solutions, and deploy models in production
Own and evolve the Dynamic Risk Score (DRS) across all markets, scoring the full client base daily
Manage transaction rules with ML-driven detection and optimize performance and generated alerts
Establish continuous monitoring of model and rule performance in production
Develop a champion-challenger framework to keep the best-performing model live
Participate in infrastructure development for ML model operationalization and inter-service interactions
Serve and infer models of varying complexity
Deploy, serve, monitor, and improve a production ML product that supports quarantine, alert suppression, and future credit decisions

Requirements

What you’ll need

At least 5 years as a Machine Learning Engineer or Full-stack Data Scientist
Production deployment experience, including API services such as FastAPI
Strong SQL and Python skills
Experience with cloud data platforms such as Databricks
Strong architectural skills; ability to design and improve infrastructure serving models of varying complexity
Experience with model monitoring and champion-challenger / A-B evaluation in production
Quantitative education in math, engineering, economics, or computer science
Full working proficiency in English
Exposure to graph modeling or foundation models/embeddings is a plus
Critical, analytical, proactive, result-driven, and comfortable working with little supervision in a start-up setting

Benefits

Comp & perks

Continuous personal and professional development resources and opportunities
Flexibility to travel and work remotely or in a hybrid model across Europe
Stock Options Program available to every team member
Constant support and care in a modern, friendly, and eco-conscious corporate culture
Work & Swim Program: one month in a corporate apartment in Cyprus