3 months ago
Limassol, CyprusSenior / Staff+
Responsibilities
- Design, develop, validate, deploy, monitor, and retrain production machine learning models end to end.
- Lead AI use cases including client lifetime value, churn prediction, and fraud or abuse detection.
- Build MLOps practices covering deployment pipelines, environment promotion, lifecycle management, monitoring, drift detection, and retraining.
- Implement model explainability using SHAP, feature attribution, and other interpretability techniques.
- Define and enforce model governance, documentation, versioning, auditability, and approval standards.
- Collaborate with Data Engineering on data pipelines, feature engineering, reproducibility, and scalable data foundations.
- Work with Product, Risk, Commercial, and other stakeholders to translate business problems into AI solutions.
- 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, including testing, code quality, modular design, and maintainability.
- Strong understanding of machine learning concepts, model evaluation, feature engineering, data leakage, drift, and model stability.
- Hands-on experience with large-scale data processing using Spark or PySpark.
- Experience with ML lifecycle tools such as MLflow for experiment tracking, model management, and reproducibility.
- Experience building and maintaining CI/CD pipelines for ML or data workflows, with GitHub Actions preferred.
- Strong SQL skills and experience working with large, complex real-world datasets.
- Demonstrated ability to deliver AI/ML solutions with measurable business impact.
- Experience with production model deployment, monitoring, drift detection, and retraining strategies.
- Strong communication skills and the ability to work with technical and non-technical stakeholders.
- Fintech, trading, financial services, real-time or streaming ML, LLMs, embeddings, retrieval-augmented generation, regulated environments, model governance, mentoring, or applied AI leadership experience is a plus.
Benefits
- Competitive remuneration package based on qualifications and experience, including a 13th salary and discretionary bonuses.
- Employee Training & Development program and opportunities for career growth.
- Medical insurance covering outpatient, inpatient, and dental care.
- Quarterly and semiannual team activities and company events.
- Provident Fund welfare investment and savings plan.
- Birthday and loyalty benefits.
- Collaboration with SportBenefit.
Tech Stack
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