Senior Machine Learning Engineer, Ad Performance

Senior Any Podgorica, Montenegro Full-time Posted 2 months ago

Skills & stack

Languages

Python

Skills

Causal Inference Pandas PyTorch scikit-learn

About the role

Senior Machine Learning Engineer, Ad Performance at Coinis. This is a full-time role based in Podgorica, Montenegro, with remote work available in EU timezones. You will build systems that turn ad metrics into creative insights and improve creative performance before spend.

Work format

Full-time. Remote work is available in EU timezones or from Podgorica, Montenegro.

Skills and tools

Python
Pandas
scikit-learn
PyTorch
Causal Inference

What to prepare

Prepare an example of production ML work with serving, monitoring, or retraining.
Bring a short walkthrough of a project that used causal inference or experimentation.
Have a sample that shows your work with Python, Pandas, scikit-learn, or PyTorch.

Responsibilities

Build the performance feedback loop from ad metrics to creative patterns.
Train models that predict creative win rate before budget allocation.
Design ranking systems for creative variants under budget constraints.
Run experiments with hold-outs, uplift tests, and counterfactual analysis.
Ship production systems and support dashboards used by the media buying team.

Requirements

Strong Python work with Pandas, scikit-learn, and PyTorch or equivalent.
Causal inference and experimentation design experience.
Production ML experience with serving, monitoring, and retraining.
Comfort with messy real-world ad performance data.
A shipping track record in ML, data science, or applied statistics.

Nice to have

Meta Marketing API data pipelines.
Contextual bandits or reinforcement learning in production.
Feature stores or MLOps tooling.
Multi-armed bandit budget allocation.

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Coinis

Product

AI-powered ad-tech platform, founded in 2013 in Podgorica, that automates ad creative generation, campaign launch and optimization for advertisers and publishers.

Location: Podgorica, Montenegro
Team size: 51-200
Remote policy: Hybrid

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