Forex / Trading

Cyprus

Tickmill Europe LTD

Data Science, BI & Analytics

 AI & Machine Learning

Are you looking for the next professional opportunity that will challenge you and advance your career? Join our team now! &nbsp;Tickmill is looking to hire a&nbsp;Senior AI/ML Engineer (AI Lead)&nbsp;to join our rapidly expanding team. The ideal candidate will be a highly hands-on and business-oriented professional, capable of designing and delivering production-grade AI systems that drive measurable business impact. &nbsp;About Tickmill. &nbsp;Tickmill is an award-winning, multi-regulated broker 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 &amp; Options). &nbsp;Founded in 2014, the&nbsp;Tickmill&nbsp;Group employs over 330 professionals across offices in London, Cyprus, Poland, Estonia, Seychelles and several other locations worldwide. &nbsp;Our culture is built on trust, transparency, and high standards.  We bring together ambitious professionals who are looking for an environment that supports them to dominate in their fields.  &nbsp;Our diverse, multilingual teams are focused on innovation, delivering bold excellence, and raising the bar wherever we can. &nbsp; &nbsp;We offer competitive benefits packages, frequent team initiatives, and opportunities for professional growth.  Join the Tigers! &nbsp;What does the role look like? &nbsp;The Senior AI/ML Engineer (AI Lead) will have the chance to:• 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. &nbsp;What do you need to succeed in this role?• 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. &nbsp;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. &nbsp; By joining us, you can expect:   &nbsp;<ul><li>A Unique Opportunity for a career in a global, fast-growing company.</li><li>Attractive&nbsp;remuneration&nbsp;package&nbsp;based on qualifications and experience (including 13th salary and Discretionary Bonuses to reward exceptional performance).&nbsp;</li><li>Opportunities to learn and grow through our “Employee Training &amp; Development program”.</li><li>Medical Insurance Cover, which includes Outpatient, Inpatient, and Dental Care.</li><li>Multiple&nbsp;events&nbsp;to bond with the team and the group through Quarterly/Semestrial Team Activities for all the Company.</li><li>Participation in our welfare investment and savings plan through our Provident Fund Scheme.</li><li>Birthday and Loyalty&nbsp;benefits.</li><li>Collaboration with SportBenefit.</li></ul>&nbsp;What to expect from our recruitment process:<ul><li>First interview with hiring managers or an HR call</li><li>Task Assessment</li><li>Technical Interview or home assignment</li><li>Final interview with top management&nbsp;</li></ul>&nbsp;

Senior AI/ML Engineer (AI Lead)

Senior AI/ML Engineer (AI Lead)

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