Data Engineer
Senior AI/ML Engineer (AI Lead)
Limassollead
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We're hiring on behalf of our client, a
Senior AI/ML Engineer
to join their team in Limassol.
Our client is an award-winning, multi-regulated broker (CySEC) offering access to a broad range of asset classes, including CFDs on Forex, Stocks, Indices, Commodities, Cryptocurrencies, and Bonds, as well as Exchange Traded Derivatives like Futures & Options.
Responsibilities:
• Design, develop, and productionise machine learning models end-to-end (training, validation, deployment, monitoring, retraining), ensuring reliability in real-world environments.
• Lead the development of AI use cases such as client lifetime value (CLV), churn prediction, and fraud/abuse detection, with clear alignment to business outcomes and measurable impact.
• Build and establish robust MLOps practices, including model deployment pipelines, CI/CD, environment promotion (dev/stage/prod), and lifecycle management.
• Implement model monitoring frameworks to track performance, data drift, data quality, and business impact, with clear retraining and escalation strategies.
• Ensure model explainability and transparency using techniques such as SHAP, feature attribution, and other interpretability methods appropriate for business-critical and regulated contexts.
• Define and enforce best practices around model governance, documentation, versioning, and auditability, proportional to model risk and business impact.
• Collaborate closely with Data Engineering to ensure high-quality data pipelines, feature engineering, reproducibility, and scalable data foundations.
• Work cross-functionally with Product, Risk, Commercial, and other stakeholders to translate business problems into pragmatic AI solutions, balancing speed and robustness.
• Drive continuous improvement through feedback loops, monitoring insights, and model retraining strategies, rather than one-off model delivery.
• 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 (not just experimentation).
• Strong Python programming skills and solid software engineering fundamentals (testing, code quality, modular design, maintainability).
• Strong understanding of machine learning concepts, model evaluation, feature engineering, and practical considerations in production systems (e.g. data leakage, drift, stability).
• Hands-on experience with large-scale data processing (Spark / PySpark).
• Experience with ML lifecycle tools (MLflow or similar) for experiment tracking, model management, and reproducibility.
• Experience building and maintaining CI/CD pipelines (GitHub Actions preferred) for ML or data workflows.
• Strong SQL skills and experience working with large, complex datasets in real-world environments.
• Proven ability to deliver AI/ML solutions with measurable business impact, not just model performance improvements.
• Experience working with model deployment, monitoring, drift detection, and retraining strategies in production systems.
• Strong communication skills with the ability to work effectively with both technical and non-technical stakeholders, translating trade-offs clearly.
• Ability to operate effectively in environments with evolving requirements, imperfect data, and delivery pressure, balancing MVP speed with production robustness.
The below are considered as a plus:
• Experience in fintech, trading, or financial services environments, particularly where models influence business-critical decisions.
• Experience with real-time or streaming ML systems.
• Familiarity with modern AI approaches such as LLMs, embeddings, or retrieval-augmented generation (RAG), particularly where applied to business workflows or integrated with structured data.
• Experience working in regulated environments and implementing model governance frameworks (e.g. auditability, explainability, approvals, documentation standards).
• Experience contributing to team standards, mentoring, or leading applied AI delivery.
Benefits:
• A Unique Opportunity for a career in a global, fast-growing company.
• Attractive remuneration package based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance).
• Opportunities to learn and grow through our “Employee Training & Development program”.
• Medical Insurance Cover, which includes Outpatient, Inpatient, and Dental Care.
• Multiple events to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company.
• Participation in our welfare investment and savings plan through our Provident Fund Scheme.
• Birthday and Loyalty benefits.
• Collaboration with SportBenefit.
Make your next Career step and apply NOW!
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Due to the great number of applications, we receive for each of our open vacancies, we are unable to respond on an individual basis.
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