What You'll Do

• Design, develop, and deploy machine learning models and solutions, leveraging tools such as LangGraph and MLflow for orchestration and lifecycle management.
• Collaborate on building and maintaining scalable data and feature pipeline infrastructure for real-time and batch processing using tools like BigQuery, BigTable, Dataflow, Composer(Airflow), PubSub, and Cloud Run to support ML model training and inference.
• Develop and implement robust strategies for model monitoring and observability to detect model drift, bias, and performance degradation, leveraging tools like Vertex AI Model Monitoring and custom dashboards.
• Optimize ML model inference performance to improve latency and cost-efficiency of AI applications.
• Ensure the overall reliability, performance, and scalability of the ML models and data infrastructure platform, including proactive identification and resolution of issues related to model performance and data quality.
• Troubleshoot and resolve complex issues impacting ML models, data pipelines, and production AI systems.
• Ensure AI/ML models and workflows meet data governance, security, and compliance requirements, specifically for real-money gaming.

What We're Looking For

• 1+ years of experience as an ML Engineer, with a focus on developing and deploying machine learning models in production environments.
• Strong experience in Google Cloud Platform (GCP), including services relevant to ML and data infrastructure such as BigQuery, Dataflow, Vertex AI, Cloud Run, and Pub/Sub and Composer (Airflow).
• Solid grasp of containerization (Docker, Kubernetes) and experience with Kubernetes orchestration platforms like GKE for deploying ML services.
• Experience building and deploying scalable data pipelines and machine learning models in production environments.
• Understanding of model monitoring, logging, and observability best practices for ML models and applications.
• Experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Familiarity with AI orchestration concepts using tools like LangGraph or LangChain is a bonus.
• Bonus experience includes working in gaming, real-time fraud detection, or AI personalization systems and Agentic workflows.