Senior AI/ML Engineer (AI Lead) - Estonia

About the role

Tickmill, a multi-regulated broker founded in 2014 with offices in London, Cyprus, Poland, Estonia and Seychelles, is hiring a Senior AI/ML Engineer (AI Lead) in Tallinn. The role is hands-on and business-oriented, focusing on designing and delivering production-grade AI systems that drive measurable business impact.

Key responsibilities

• Design, develop and productionise machine learning models end-to-end, including training, validation, deployment, monitoring and retraining.
• Lead AI use cases such as client lifetime value, churn prediction and fraud/abuse detection, aligned to business outcomes.
• Build MLOps practices: deployment pipelines, CI/CD, environment promotion and lifecycle management.
• Implement model monitoring for performance, data drift, data quality and business impact, with retraining and escalation strategies.
• Ensure model explainability and transparency using techniques such as SHAP and feature attribution.
• Define model governance, documentation, versioning and auditability, proportional to model risk.
• Work with Data Engineering on data pipelines, feature engineering and reproducibility, and with Product, Risk, Commercial and other stakeholders.
• Mentor team members and promote best practices in production AI and MLOps.

Required profile

• 5-8+ years of experience building and deploying machine learning models in production.
• Proven ability to deliver AI/ML solutions with measurable business impact.
• Strong communication skills with technical and non-technical stakeholders.
• Ability to balance MVP speed with production robustness under evolving requirements and delivery pressure.

Required skills

• Strong Python and software engineering fundamentals (testing, code quality, modular design).
• Machine learning concepts, model evaluation, feature engineering and production considerations such as data leakage and drift.
• Large-scale data processing with Spark / PySpark.
• ML lifecycle tools such as MLflow.
• CI/CD pipelines (GitHub Actions preferred) and strong SQL.
• Model deployment, monitoring, drift detection and retraining.

Nice to have: fintech or regulated-environment experience, streaming ML, LLMs/embeddings/RAG, and mentoring or leadership experience. The process includes an HR interview, an assessment task, interviews with hiring managers and a final interview with top management.