Define the strategic approach for scalable, high-performing machine learning pipelines across online and offline feature workflows

Architect advanced machine learning models with Python, TensorFlow, and cutting-edge frameworks

Lead optimization and deployment of enterprise-grade inference pipelines focused on real-time applications like player telemetry analytics

Enforce standardized machine learning workflows by incorporating tools such as MLflow within cross-functional teams

Oversee robust data integration pipelines built on ETL/ELT frameworks in enterprise-level environments using Databricks

Establish the vision for reliable and scalable production-grade ML systems with continuous optimization in focus

Develop automated and dependable solutions for complex feature engineering processes and seamless model deployment systems

Collaborate with senior stakeholders to align organizational KPIs with machine learning strategies at scale

Drive innovation around dataset management and computational workflows utilizing Databricks infrastructure

Promote best practices and innovation for scalable, high-efficiency ML solutions across the enterprise

7+ years of relevant expertise in scalable machine learning systems within intricate environments

2+ years in recognized leadership roles managing ML teams or major initiatives

Proficiency in Databricks, MLflow, TensorFlow, and advanced data engineering platforms

Advanced skills in Python, prioritizing ML, data optimization, and engineering processes

Background in ETL/ELT methodologies and integrating large-scale data pipelines

Showcase of optimizing real-time data systems requiring low-latency and exceptional reliability

Competency in scaling advanced feature engineering workflows for enterprise-level applications

Qualifications in managing ML model lifecycles within demanding production setups

Understanding of building solutions that balance scalability, efficiency, and maintainability across critical systems

Proficiency in English communication, both written and verbal, at a C1 level or higher

Knowledge of recommender systems tailored for content discovery and improving user engagement

Understanding of machine learning infrastructure deployment on AWS, GCP, or similar cloud platforms

Showcase of expertise in real-time analytics and creating telemetry-driven systems across large-scale operations