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Globaldev Group

Senior Machine Learning Engineer

Reposted 11 Days Ago
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Remote
Hiring Remotely in Poland
Senior level
Remote
Hiring Remotely in Poland
Senior level
Design and scale predictive ML systems for VIS.X, taking end-to-end ownership of various high-impact ML initiatives and shaping the ML architecture.
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We are looking for a Senior Machine Learning Engineer to design, own, and scale predictive systems that power VIS.X - programmatic advertising platform.
You will take end-to-end responsibility for high-impact ML initiatives (e.g., pricing optimization, bid prediction, performance forecasting, delivery optimization) and translate complex business problems into robust, production-grade machine learning systems.
This is a senior individual contributor role with leadership potential. You will help shape our ML architecture, standards, and long-term AI strategy, with the opportunity to grow into a team lead role as we expand our data science capabilities.

Requirements:
  • 5+ years of experience in machine learning / applied ML roles with production ownership
  • Proven track record of deploying and maintaining ML systems in real-world environments
  • Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)
  • Solid knowledge of statistics, experimentation design, and model evaluation
  • Experience working with large-scale datasets and performance-critical systems
  • Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)
  • Strong problem ownership mindset - ability to independently structure ambiguous challenges
  • Ability to translate business trade-offs into modeling decisions
  • Experience in AdTech, marketplaces, or auction-based systems is a plus
  • Experience working in high-scale, real-time systems is a plus
Responsibilities:
  • Take ownership of machine learning problems from concept to production
  • Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)
  • Develop scalable feature engineering and data pipelines for large-scale datasets
  • Define experimentation frameworks (A/B testing, offline validation, model comparison)
  • Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability
  • Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact
  • Quantify model impact on revenue, margin, and performance KPIs
  • Contribute to building our long-term ML architecture and best practices
What we offer:
  • Comfortable environment, challenging tasks and a long-term interesting project;
  • Covered 20 days of vacation;
  • Working with top notch equipment;
  • Bookkeeping by a professional accountant;
  • Help and support from our caring HR-team;

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