GR8 Tech builds B2B iGaming platforms for operators who play to lead.
We deliver full-cycle, high-impact tech designed to scale — from seamless integrations and expert consulting to long-term operational support. Our platform powers millions of active players and drives real business growth. Call it what it is: the iGaming Platform for Champions.
With 1000+ GR8 people across locations and time zones, we don’t just ship technology — we help operators build success stories across brands, markets, and geos.
Our ambition drives us. Our people make it real.
If you’re a challenger in spirit and a champion in action — join us.Why this role exists:
We are growing our AI/ML team and are looking for a Senior Machine Learning Engineer to take a leading role in building and scaling applied machine learning systems that power personalization and discovery features across our platform. A key initiative is a large-scale recommendation system based on a two-tower architecture, deployed on AWS and serving millions of users. This position is not limited to a single use case. You will also contribute to other machine learning and data science initiatives, helping define best practices and raising the overall ML maturity of the team.
What you’ll drive:
Technical Leadership & Ownership
Take technical ownership of core components of recommendation and personalization systems (retrieval, ranking, evaluation).
Design and evolve two-tower / embedding-based retrieval models and downstream rankers.
Drive architectural and modeling decisions with a strong understanding of trade-offs between model quality, system complexity, latency, and cost.
Define and promote best practices for ML system design, experimentation, evaluation, and deployment.
Review ML designs, pipelines, and code with a focus on correctness, maintainability, and production readiness.
Act as a technical point of reference for ML-related decisions within the team
Hands-on ML Development
Develop, train, and improve ML models for retrieval and ranking use cases.
Work with embedding-based deep learning models and classical ML approaches.
Perform in-depth data analysis, feature exploration, and systematic error analysis.
Build reproducible experiments and robust offline evaluation pipelines.
Optimize models for both offline metrics and online business KPIs.
Design and operate batch and real-time training and inference workflows in a cloud environment, with awareness of scalability and cost trade-offs.
Experimentation & Production
Design, run, and analyze offline experiments and online A/B tests.
Own ML components in production, with a strong focus on reliability, observability, and safe iteration.
Monitor model performance and data quality in production.
Collaborate on scalable training and serving infrastructure for ML systems.
Participate in incident analysis related to ML systems and contribute to root-cause analysis and long-term fixes.
Design ML systems with failure modes in mind, including fallbacks and graceful degradation.
Collaboration & Mentorship
Work closely with Data Engineering on data pipelines and feature generation.
Partner with Product and Analytics to translate business goals into clear ML objectives and success metrics.
Act as a technical mentor for ML engineers, providing guidance on modeling, experimentation, and production ML.
Provide constructive feedback through code reviews and design discussions, supporting the growth of the team.
What makes you a GR8 fit:
Must-have
5+ years of experience in Machine Learning / Applied Data Science.
Strong Python skills and experience writing production-quality ML code.
Solid foundation in core ML and data science tools: NumPy, Pandas, scikit-learn, etc.
Hands-on experience with deep learning frameworks (PyTorch or TensorFlow).
Practical experience with embedding models and similarity-based retrieval.
Experience with tree-based models (LightGBM, XGBoost).
Strong understanding of ML evaluation, experimentation, and applied statistics.
Experience deploying, operating, and maintaining ML models in production environments.
Proficiency with Git, Linux, Docker, and standard ML development workflows.
Practical experience deploying ML systems in a cloud environment (AWS or equivalent).
Nice-to-have
Direct experience with recommendation systems or search-related problems.
Experience designing or operating two-tower / dual-encoder architectures.
Familiarity with ANN methods and large-scale retrieval (e.g., FAISS or equivalents).
Understanding of common ML production challenges (training–serving skew, data leakage, model drift).
Experience collaborating on data pipelines and feature engineering at scale.
Experience leading or mentoring other ML engineers.
Experience with experiment automation and hyperparameter optimization (Optuna, Ray /Tune, Hyperopt, or cloud-native equivalents).
Background in high-scale consumer products (content, gaming, media, marketplaces).
Experience working with CI/CD pipelines for ML workflows (training, evaluation, deployment).
Tech Stack
Languages: Python, SQL.
Core ML / DS: NumPy, Pandas, scikit-learn.
Deep Learning: PyTorch / TensorFlow.
ML Models: LightGBM, XGBoost.
Retrieval: Embeddings, ANN.
Cloud & Data: AWS, SageMaker, S3, Glue.
Dev & MLOps: Git, Docker, Linux.
Why you’ll love working here:
Benefits Cafeteria — annual budget you allocate to:
Sports • Medical • Mental health • Home office • Languages.
Work-life & support
Paid maternity/paternity leave + monthly childcare allowance.
20+ vacation days, unlimited sick leave, emergency time off.
Remote-first + tech support + coworking compensation.
Team events (online/offline/offsite).
Learning culture with internal courses + growth programs.
Our culture & core values:
GR8 Tech culture is how we win — through trust, ownership, and a growth mindset. We move fast, stay curious, and keep it real, with open feedback, room to experiment, and a team that’s got your back.
FUELLED BY TRUST: we’re open, honest, and have each other’s backs.
OWN YOUR GAME: we take initiative and own what we do.
ACCELER8: we move fast, focus smart, and keep it simple.
CHALLENGE ACCEPTED: we grow through challenges and stay curious.
BULLETPROOF: we’re resilient, ready, and always have a plan.