Senior AI/ML Engineer – Applied AI Lead

Cross Border Talents; Warszawa; Sur place; PLN 315 000 - 384 000; Plein temps

Avantages offerts par ce poste

Remuneration package

Training & Development

Team events

Birthday benefits

Résumé du poste

Cross Border Talents is seeking a Senior AI/ML Engineer to lead applied AI initiatives on-site in Tallinn. The role focuses on designing, deploying and monitoring ML models with strong emphasis on MLOps and governance. You will collaborate with data engineering and business stakeholders to deliver measurable impact.

The ideal candidate has 5–8+ years of hands-on ML experience, deep Python expertise and experience with Spark/PySpark, MLflow and CI/CD pipelines in production environments.

Qualifications

• 5–8+ years of experience building and deploying machine learning models in production environments.
• Strong Python programming skills and solid software engineering fundamentals.
• Strong understanding of machine learning concepts, model evaluation and feature engineering.
• Practical understanding of production ML considerations including data leakage, drift and model stability.

Responsabilités

• Design, develop and productionise machine learning models across training, validation, deployment, monitoring and retraining.
• Lead AI use cases including client lifetime value, churn prediction and fraud or abuse detection.
• Build and establish robust MLOps practices, including deployment pipelines, CI/CD, environment promotion and model lifecycle management.
• Implement model monitoring frameworks covering performance, data drift, data quality and business impact.
• Establish retraining and escalation strategies for production models.
• Implement model explainability and transparency using SHAP, feature attribution and other interpretability techniques.
• Define and enforce best practices around model governance, documentation, versioning and auditability.
• Collaborate with Data Engineering on data pipelines, feature engineering, reproducibility and scalable data foundations.
• Partner with Product, Risk, Commercial and other stakeholders to translate business problems into pragmatic AI solutions.
• Drive continuous improvement through monitoring insights, feedback loops and model retraining.
• Mentor team members and promote best practices in production AI, MLOps and applied machine learning delivery.

Connaissances

Python

Software engineering

ML concepts

Spark/PySpark

MLflow

CI/CD

SQL

Stakeholder communication

Outils

Spark / PySpark

MLflow

GitHub Actions

Description du poste

Position: Senior AI/ML Engineer – Applied AI Lead
Location: Tallinn,Estonia
Work model: On-site
Employment type: Full-time
Salary:Up to 80,000 Euros gross yearly + other benefits

DUTIES AND RESPONSIBILITIES:

• Design, develop and productionise machine learning models across training, validation, deployment, monitoring and retraining
• Lead AI use cases including client lifetime value, churn prediction and fraud or abuse detection
• Build and establish robust MLOps practices, including deployment pipelines, CI/CD, environment promotion and model lifecycle management
• Implement model monitoring frameworks covering performance, data drift, data quality and business impact
• Establish retraining and escalation strategies for production models
• Implement model explainability and transparency using SHAP, feature attribution and other appropriate interpretability techniques
• Define and enforce best practices around model governance, documentation, versioning and auditability
• Collaborate with Data Engineering on data pipelines, feature engineering, reproducibility and scalable data foundations
• Partner with Product, Risk, Commercial and other stakeholders to translate business problems into pragmatic AI solutions
• Drive continuous improvement through monitoring insights, feedback loops and model retraining
• Mentor team members and promote best practices in production AI, MLOps and applied machine learning delivery

REQUIREMENTS:

• 5–8+ years of experience building and deploying machine learning models in production environments
• Strong Python programming skills and solid software engineering fundamentals
• Strong understanding of machine learning concepts, model evaluation and feature engineering
• Practical understanding of production ML considerations including data leakage, drift and model stability
• Hands‑on experience with Spark / PySpark and large-scale data processing
• Experience with MLflow or similar ML lifecycle tools
• Experience building and maintaining CI/CD pipelines, preferably with GitHub Actions
• Strong SQL skills and experience working with large, complex datasets
• Proven ability to deliver AI/ML solutions with measurable business impact
• Experience with model deployment, monitoring, drift detection and retraining strategies
• Strong communication skills with both technical and non-technical stakeholders
• Ability to balance MVP delivery speed with production robustness in evolving environments

OFFER:

• Attractive remuneration package based on qualifications and experience
• Employee Training & Development programme
• Multiple team and group events
• Birthday and loyalty benefits
• And much more!