Senior Machine Learning Engineer
- Hiring location
- Remote
- Compensation
- Pay not listed
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:
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5+ years of experience in machine learning / applied ML roles with production ownership
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Proven track record of deploying and maintaining ML systems in real-world environments
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Strong Python skills (e.g., pandas, scikit-learn, PyTorch/TensorFlow)
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Solid knowledge of statistics, experimentation design, and model evaluation
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Experience working with large-scale datasets and performance-critical systems
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Understanding of MLOps principles (model lifecycle, monitoring, CI/CD integration, retraining pipelines)
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Strong problem ownership mindset - ability to independently structure ambiguous challenges
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Ability to translate business trade-offs into modeling decisions
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Experience in AdTech, marketplaces, or auction-based systems is a plus
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Experience working in high-scale, real-time systems is a plus
Responsibilities:
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Take ownership of machine learning problems from concept to production
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Design, build, and deploy predictive models (e.g. pricing, bidding, optimization, forecasting)
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Develop scalable feature engineering and data pipelines for large-scale datasets
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Define experimentation frameworks (A/B testing, offline validation, model comparison)
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Ensure production-grade MLOps: monitoring, retraining, drift detection, reliability
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Collaborate closely with DevOps, Product, Engineering teams to align ML with business impact
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Quantify model impact on revenue, margin, and performance KPIs
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Contribute to building our long-term ML architecture and best practices
What we offer:
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Comfortable environment, challenging tasks and a long-term interesting project;
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Covered 20 days of vacation;
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Working with top notch equipment;
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Bookkeeping by a professional accountant;
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Help and support from our caring HR-team;