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Senior AI/ML Engineer – Applied AI Lead (REF DSR :111)

Cross Border Talents · Warsaw, Poland

Strong hiring record · median 16 days open

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Actively hiring

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Senior AI/ML Engineer – Applied AI Lead (REF DSR :111) at Cross Border Talents. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

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!

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