Machine Learning Engineer supporting the Enterprise Machine Learning team in developing advanced solutions. Collaborating with stakeholders and driving data science initiatives in a hybrid work environment.
About the role
- Machine Learning Engineer responsible for ML model design and deployment at SiGMA Group. Enhancing event experiences through AI-driven solutions in iGaming and tech.
Responsibilities
- The Machine Learning Engineer is responsible for designing, building, deploying, and maintaining machine learning models and AI‑driven systems that enhance the Sigma Groups global event experiences, including major iGaming events.
- Build, train, optimise, and deploy machine learning models for use cases such as personalised event recommendations, attendee behaviour prediction, exhibitor and sponsor performance forecasting, churn and retention modelling, and anomaly detection for event operations.
- Implement model monitoring, retraining pipelines, and performance optimisation.
- Introduce and integrate AI tooling that enhances engineering and operational workflows, including automated model evaluation, AI‑assisted feature engineering, and intelligent monitoring and diagnostics.
- Collaborate with data engineers to build and maintain robust data pipelines for model training and inference.
- Ensure data quality, consistency, and availability across event systems, CRM platforms, mobile apps, and iGaming‑related tools.
- Develop ML solutions tailored to the unique dynamics of live events and iGaming audiences. Support real‑time inference systems that handle high‑traffic spikes during major events. Build models that enhance attendee engagement, exhibitor value, and partner insights.
- Ensure ML systems comply with data‑privacy regulations and responsible‑gaming requirements where applicable. Implement responsible‑AI practices, including bias detection, explainability, and ethical model usage.
- Work closely with data scientists, data engineers, product managers, and platform teams to deliver end‑to‑end AI solutions. Translate business requirements into technical ML specifications.
Requirements
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit‑learn)
- Experience with cloud‑based ML platforms and MLOps tools
- Strong understanding of data engineering, distributed systems, and real‑time processing
- Familiarity with AI‑assisted development tools and emerging ML technologies
- Excellent problem‑solving and analytical skills
- Ability to work effectively in cross‑functional teams
- Experience with event‑driven or iGaming data is a plus
- Educated to degree level in a numerate or technical discipline, Masters preferred.
- 5-7+ years of technical experience in machine learning, AI engineering, or related fields
- 1-2+ years of management or mentorship experience, such as leading ML projects or guiding junior engineers
- Proven track record of deploying ML models into production environments
- Experience supporting AI‑enabled products or automation initiatives
- Background working with event data, digital engagement metrics, or iGaming systems
- Experience with MLOps, CI/CD for ML, and scalable cloud architectures
Benefits
- Free iGaming Academy access -Learn the ins and outs of the industry with access to courses.
- Travel perks - Visit our international offices and attend industry events worldwide.
- Performance rewards - High performers are recognized and fast-tracked with annual reviews and bi-yearly performance checks ins.
- Interest-free car loan after probation (T&Cs apply)
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