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 • BulgariaSeniorWebsite

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. Capable of managing model performance and infrastructure while maintaining a proactive and analytical approach in a fast-paced environment.

Highest-signal resume keywords

Machine Learning EngineeringFull-Stack Data ScienceProduction DeploymentSQLPython

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Hard Skills

Machine Learning ModelsBinary ClassificationRegressionModel MonitoringChampion-Challenger FrameworkAPI ServicesFastAPICloud Data PlatformsDatabricksInfrastructure Design

Soft Skills

Critical ThinkingAnalytical SkillsProactive AttitudeResult-DrivenComfortable Working Independently

Industry Keywords

Financial Crime DetectionDynamic Risk ScoreTransaction ProcessingClient OnboardingModel Operationalization

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, 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 alert volumes
Establish continuous monitoring of model and rule performance in production
Develop the champion-challenger framework to keep the best-performing model live
Participate in infrastructure development for ML model operationalization and inter-service interactions
Deploy, serve, monitor, and improve production models on a small team

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 thinker; 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 within a modern, friendly, and eco-conscious corporate culture
Work & Swim Program: one month in a corporate apartment in Cyprus