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 • LithuaniaSeniorWebsite

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 and infrastructure design, ensuring optimal performance and decision-making support across the client lifecycle.

Highest-signal resume keywords

Machine Learning EngineeringProduction DeploymentSQLPythonModel Monitoring

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Hard Skills

Machine LearningBinary ClassificationRegressionModel DeploymentAPI ServicesInfrastructure DesignQuantitative AnalysisGraph ModelingChampion-Challenger FrameworkData Science

Soft Skills

Proactive Work EthicResult-DrivenAbility to Work Independently

Tools & Technologies

FastAPIDatabricks

Industry Keywords

Financial Crime DetectionDynamic Risk ScoreClient OnboardingTransaction ProcessingAlert 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, and deploy models in production
Own and evolve the Dynamic Risk Score (DRS) across all markets, scoring the full client base daily
Support decision-making across the client lifecycle, including quarantine, alert suppression, and future credit decisions
Manage transaction rules with ML-driven detection and optimize performance and alert volumes
Establish continuous production monitoring for model and rule performance
Develop a champion-challenger framework to keep the best-performing model live
Participate in infrastructure development for ML 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, including designing and improving 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, result-driven, and 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