Founding Machine Learning Engineer (Recommendations + GenAI)

About the Position

Are you ready to take your Machine Learning skills to the next level?

We are hiring a Founding Machine Learning Engineer to own the intelligence layer of our products. You will design, build, and improve the models and decision systems behind recommendations, ranking, personalisation, retrieval, agent behaviour, and selected predictive analytics use cases. You will work directly with the founders to turn ambiguous product ideas into production systems that create measurable customer value. In a team of our size, this is an end-to-end role: you may touch data exploration, modelling, evaluation, experimentation, and production iteration in the same week.

This is not a pure research role. We care about people who can move from data and hypotheses to shipped systems and business impact.

Responsibilities

• Design, build, and improve ML systems for recommendations, ranking, personalisation, retrieval, and GenAI workflows;
• Turn product goals into concrete ML problems, evaluation plans, experiments, and shipped features;
• Work with behavioural, transactional, contextual, and unstructured data to identify signals and improve model quality;
• Build offline evaluation frameworks and online experiments to measure relevance, quality, latency, cost, and business impact;
• Improve GenAI agent behaviour through better retrieval, context management, prompting, tool use, orchestration, and evaluation;
• Investigate failure modes, run error analysis, and make practical tradeoffs across quality, reliability, speed, and complexity;
• Partner closely with platform and backend engineers to deploy, monitor, and iterate on models in production;
• Help define how the company does ML: metrics, experimentation discipline, technical standards, and long-term direction;
• Work with real-time behavioural and transactional signals to improve recommendations, personalisation, and intelligent product behaviour;
• Contribute to predictive and insight-driven ML use cases such as segmentation, churn prediction, recommendation measurement, and opportunity ranking;
• Write clean, testable Python and contribute reusable ML components and shared libraries used across the platform.

Requirements

• Strong foundations in machine learning, statistics, computer science, or a similar quantitative discipline;
• Experience building and shipping ML systems or intelligent product features in production or near-production environments;
• Strong Python skills and comfort working across data, modelling, evaluation, and production collaboration;
• Good understanding of experimentation, model evaluation, feature engineering, data quality, and error analysis;
• Clear communication and the ability to work through messy, ambiguous product problems;
• High ownership, self-direction, and a strong bias toward action;
• 5+ years building and shipping ML systems or intelligent product features in production;
• Strong understanding of model evaluation, cross-validation, feature engineering, and data quality challenges in real-world environments;
• Experience working with large-scale behavioural, transactional, or contextual data;
• Strong software engineering habits, including writing clean, testable, maintainable Python code.

Nice to Have

• Experience with recommendation systems, ranking, search, personalisation, or marketplace/feed optimisation;
• Experience with LLM applications, RAG, GenAI agents, prompt iteration, or evaluation of GenAI systems;
• Experience running A/B tests or online experiments;
• Experience working closely with product teams and translating user problems into ML solutions;
• Experience with real-time ML, streaming features, low-latency inference, or online learning;
• Experience with causal inference, uplift modelling, multi-armed bandits, or other decision-optimisation methods;
• Familiarity with cloud ML infrastructure, containerised deployment, and MLOps workflows;
• Experience in iGaming, fintech, e-commerce, or another domain with large-scale transactional and behavioural data;
• Experience with predictive analytics use cases such as segmentation, churn prevention, LTV modelling, or opportunity prioritisation.

We Offer

• Zero bureaucracy
• Unlimited holidays
• Medical insurance
• Only top talent and top salaries
• Challenging projects and tasks
• Smartest colleagues in the industry

About the Company

Gamingtec is an international brand that develops complete B2B software solutions for the iGaming industry. The company’s services are compliant in the following jurisdictions, including, but not limited to:

• Curaçao
• Isle of Man
• Anjouan
• Portugal
• Poland
• Mexico

Gamingtec is not a legal entity but a trading name used by various legal entities. Project Management and Consultancy Services are provided by EG Interactive LTD, a brand registered in England – 71-75 Shelton Street, Covent Garden, London, United Kingdom, WC2H 9JQ. All content on this website is protected by international trademark laws, and we reserve all rights contained therein.

How to Apply

Sounds interesting? Do not hesitate to apply or contact us if you have any questions!

Interview Process

• A 30-minute interview with a member of our HR team to get to know you and your experience;
• A 1-hour technical interview;
• A final interview to gauge your fit with our culture and working style.