Staff Machine Learning Engineer - Applied ML

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July 24

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Happening

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Gaming • Fintech • B2C

Happening is a technology-driven company that is redefining the sports betting landscape through innovative platforms and applications. By transforming the way users experience sports betting, Happening serves as the technology engine behind Superbet's global brands, facilitating a thrilling interaction for millions of users worldwide. The company embraces engineering excellence to create not just a platform for betting but an engaging experience that challenges industry norms.

501 - 1000 employees

Founded 2022

🎮 Gaming

💳 Fintech

👥 B2C

📋 Description

• Identify high-impact ML opportunities and influence stakeholders to prioritize and support these initiatives. • Design and develop scalable machine learning models — including classifiers, regressors, and rule-based systems — to solve real-world problems. • Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment. • Translate complex technical concepts into clear insights for both technical and non-technical stakeholders. • Set and guide technical direction across ML projects, ensuring technical best practices as well as alignment with business goals. • Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement.

🎯 Requirements

• 7+ years of industry experience building and deploying ML models at scale. • Proven ability to lead cross-functional technical initiatives and influence engineering strategy. • Proficiency in Python (with libraries like PyTorch, XGBoost, Scikit-learn) and SQL. • Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar. • Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies. • A track record of shipping production-level ML products and maintaining high code quality. • Excellent problem-solving skills and ability to scope and disambiguate complex ML projects into clear, achievable milestones.