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Senior Machine Learning Engineer

Globaldevgroup

Apply at GlobaldevgroupOpens the employer's own posting.
Where
Remote · Poland (Remote)
Level
Senior
Salary
not stated by the employer
Technologies
Python
First sniffed
29 Oct 2026 03:45 · open 27h
Last verified
30 Oct 2026 04:31 · still on the employer's site
Source
Company careers system

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;