Senior Machine Learning Engineer (copy)

FinomVilnius, VilniusRemote, HybridFull-timeSenior, 5–8 yearsListed 1 month ago

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About this role

At Finom, we're transforming how small and medium businesses across Europe manage their money - and financial crime prevention sits right at the heart of that promise. As a Senior Machine Learning Engineer, you'll take over DRS: a production ML product that scores our whole client base daily and drives our quarantine, alert suppression, and soon our credit decisions. This is genuine end-to-end ownership on a small team - you'll deploy, serve, monitor, and improve the system rather than inherit a finished one. If you're the kind of engineer who quietly keeps production models honest and wants their decisions to actually reach live traffic, this is your seat.

What You Will Be Doing

- Full-stack ML model development (binary classification and regression) for the detection and prevention of financial crime during transaction processing and client onboarding: gathering requirements, prototyping, and deployment in a production environment.

- Own and evolve the Dynamic Risk Score (DRS) across all markets — daily scoring of the full client base that feeds decisioning across the client lifecycle.

- Handle a portfolio of transaction rules with ML-driven detection inside, optimizing their performance and the number of generated alerts.

- Set up continuous monitoring of model and rule performance in production, and develop the champion-challenger framework so the best-performing model is always the one live in production.

- Participate in infrastructure development for ML model operationalization and inter-service interactions, so models of varying complexity can be served and inferred.

Who You Are

- At least 5 years as a Machine Learning Engineer or Full-stack Data Scientist, with production deployment experience (incl. API services like FastAPI).

- Strong in SQL and Python, and with cloud data platforms (e.g. Databricks).

- Strong architectural skills — able to design and improve infrastructure that serves models of varying complexity.

- Experience with model monitoring and champion-challenger / A-B evaluation in production. Exposure to graph modeling or foundation models/embeddings is a plus.

- Critical, analytical thinker — proactive, result-driven, comfortable working with little supervision in a start-up setting.

- A quantitative education (math, engineering, economics, or CS) and full working proficiency in English.

What You Will Get In Return
 
Make a genuine impact on the product
 
Join our upward trajectory, and grow with us. We provide the resources and opportunities for continuous personal and professional development, empowering you to make a genuine impact on our evolving product.
 
Work in the EU
 
Embark on this exciting journey with us and enjoy the flexibility of traveling and working remotely or in a hybrid model across Europe.
 
Become a stock options holder
 
Unlock your inner entrepreneur and align your aspirations with ours through our Stock Options Program. This exciting opportunity is available to every team member, from junior team members to our founders.
 
Receive unwavering support and care
 
Finom stands by you at every step, embodying our commitment to your well-being and success reflected in our modern, friendly, and eco-conscious corporate culture. We offer constant support and care to ensure your Finom experience is successful and fulfilling.
 
Work & Swim program
 
Immerse yourself in our exclusive Work & Swim Program. Spend one month in a comfortable corporate apartment in enchanting Cyprus. It's the ideal opportunity to strike the perfect work-life balance while enjoying breathtaking Mediterranean views.
 
Equal Opportunity Statement 
 
At Finom, we're an equal opportunity employer and value diversity at our company. We embrace diversity and invite applications from all walks of life. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, disability status, or other applicable legally protected characteristics.