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 • SpainSeniorWebsite

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 and optimization, with a solid foundation in quantitative disciplines.

Highest-signal resume keywords

Machine Learning EngineeringProduction DeploymentSQLPythonCloud Data Platforms

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Hard Skills

Machine Learning ModelsBinary ClassificationRegressionModel MonitoringChampion-Challenger FrameworkAPI ServicesFastAPIInfrastructure DevelopmentGraph ModelingQuantitative Analysis

Soft Skills

Proactive Work EthicIndependent Problem Solving

Tools & Technologies

DatabricksCloud PlatformsML Operationalization

Industry Keywords

Financial Crime DetectionTransaction ProcessingClient OnboardingDynamic Risk ScoreClient Lifecycle

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
Score the full client base daily to support decision-making across the client lifecycle
Manage transaction rules with ML-driven detection and optimize their performance and alert volume
Establish continuous monitoring of model and rule performance in production
Develop a champion-challenger framework to keep the best-performing model live
Contribute to infrastructure development for ML model operationalization and inter-service interactions
Deploy, serve, monitor, and improve the production ML product

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 like 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
Ability to work proactively and independently in a start-up setting

Benefits

Comp & perks

Continuous personal and professional development resources and opportunities
Remote or hybrid work flexibility across Europe
Stock Options Program for every team member
Modern, friendly, and eco-conscious corporate culture
Constant support and care
Work & Swim Program: one month in a corporate apartment in Cyprus