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 • SerbiaSeniorWebsite

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 and Python. Proficient in model monitoring, infrastructure development, and production deployment, ensuring optimal performance and compliance in a dynamic environment.

Highest-signal resume keywords

Machine Learning EngineeringFull-Stack Data ScienceProduction DeploymentSQLPython

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Hard Skills

Machine Learning ModelsBinary ClassificationRegressionAPI ServicesFastAPIModel MonitoringChampion-Challenger FrameworkQuantitative AnalysisGraph ModelingFoundation Models

Soft Skills

Critical ThinkingAnalytical SkillsProactive AttitudeResult-DrivenComfortable with Little Supervision

Tools & Technologies

DatabricksCloud Data Platforms

Industry Keywords

Financial Crime DetectionTransaction ProcessingClient OnboardingDynamic Risk ScoreInfrastructure Development

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 across all markets, scoring the full client base daily
Manage transaction rules with ML-driven detection and optimize performance and alert volume
Establish continuous production monitoring for model and rule performance
Develop a champion-challenger framework to keep the best-performing model live in production
Participate in infrastructure development for ML model operationalization and inter-service interactions
Serve and infer models of varying complexity

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 for 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, and result-driven; comfortable working with little supervision in a start-up setting

Benefits

Comp & perks

Continuous personal and professional development opportunities
Remote or hybrid work flexibility across Europe
Stock Options Program available to every team member
Supportive, modern, friendly, and eco-conscious corporate culture
Work & Swim Program: one month in a corporate apartment in Cyprus