At Papaya, we believe in the power of play. We are one of the world's fastest-growing mobile game companies, providing entertainment for millions of users across multiple apps. We are building the most exciting players' community in the world by turning everyday moments into thrilling social tournaments.
About the Role: We are looking for a highly autonomous Senior Machine Learning Engineer to join our dedicated AI-ML Team.
Our team is responsible for developing cutting-edge Machine Learning and Data Science solutions that drive the company forward.
In this senior role, you will be expected to tackle our most complex algorithmic challenges and drive projects forward independently. Your primary focus will be researching, designing, and creating advanced ML models, with a strong emphasis on prediction-based solutions. We believe in end-to-end ownership. While your core expertise is deeply rooted in machine learning and data science, you will also handle the necessary engineering tasks to bring your solutions to life, writing the code to integrate your models into our backend production systems.
What you'll do
Independently research, design, train, and evaluate complex machine learning models, specifically focusing on predictive analytics that impact our products and players.
Take full ownership of hard technical data science problems, driving ML solutions from ideation and architecture to production without requiring heavy oversight.
Analyze and process large, complex datasets to engineer features, extract actionable insights, and continuously improve model accuracy.
Handle the basic backend engineering required to deploy your models, such as writing APIs to serve predictions to our live environments.
Mentor peers, set best practices for the AI-ML team, and continuously monitor, maintain, and optimize production models.
Requirements
MSc or PhD in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field (focus on Machine Learning or Data Science).
Proven senior-level experience (typically 4+ years) as a Machine Learning Engineer or Data Scientist with a strong portfolio of building predictive models from scratch.
Demonstrated ability to work independently, architect ML solutions, and solve highly difficult data science problems.
High proficiency in Python and industry-standard machine learning frameworks (e.g., PyTorch, TensorFlow, scikit-learn, XGBoost).
End-to-End Engineering Capability: Solid foundation in backend engineering (e.g., Python frameworks like FastAPI/Flask, Node.js) with the ability to build the API infrastructure needed to deploy your models into production.
Extensive experience working with SQL/NoSQL databases and building robust data pipelines.
A practical, "get-things-done" mindset. You care more about delivering a working, impactful solution than strictly staying within the boundaries of traditional research.
Excellent problem-solving skills and an ability to communicate complex data concepts clearly to both technical and non-technical stakeholders.
Nice to have
Strong Advantage: Previous experience in the mobile gaming industry or large-scale B2C applications.
Experience with ML platforms and managed cloud services like Google Vertex AI or AWS SageMaker.
Familiarity with modern frontend frameworks (React, Vue) for spinning up quick internal dashboards.