Senior ML Engineer / Data Scientist (AI)

Location: Fully remote across Europe, Albania, Poland, Romania, and Ukraine

Company

Creates technology solutions for global customers, including high-scale products using modern AI technologies.

What you will do

• Design and develop a self-learning Postlog and Prelog recognition system using machine learning and large language models.
• Build versioned prompts, evaluation datasets, few-shot examples, and production-grade extraction and grounding workflows.
• Run evaluation pipelines and shadow-mode comparisons while improving recognition quality, layout mapping, and model behavior.
• Develop entity-matching systems for Station, Advertiser, and CreativeID master data with confidence scoring, thresholding, and auditability.
• Monitor confidence, latency, operational quality, infrastructure costs, and prompt or model drift.
• Collaborate with Data Engineering teams and customer stakeholders on ML integration, operationalization, and technical recommendations.

Requirements

• At least 5 years of experience in machine learning, data science, or ML engineering.
• Production experience delivering ML models or LLM-powered systems, including prompt engineering, versioning, evaluation, and grounding.
• Strong Python and SQL skills, with solid knowledge of statistics, confidence estimation, sampling, hypothesis testing, and threshold optimization.
• Experience with classification, ranking, matching, or recommendation problems and with offline evaluation, validation, and production monitoring.
• Hands-on AWS experience, including S3, IAM, CloudWatch, and orchestration services.
• Upper-Intermediate English level or higher, plus strong communication and collaboration skills.

Nice to have

• Experience with Amazon Bedrock or equivalent enterprise LLM platforms and Claude/Sonnet-class models.
• Experience with Excel or layout extraction systems.
• Knowledge of confidence calibration, active learning, weak supervision, or cost-aware LLM operations.
• Advertising or media domain knowledge.
• Familiarity with Glue, Airflow, or similar orchestration and data pipeline tools.

Culture & Benefits

• Fully remote work across the stated European locations.
• Significant ownership of production AI systems and challenging engineering tasks.
• Opportunity to influence high-scale automation and machine learning products.
• Collaboration with Data Engineering teams and customer stakeholders.