We are searching for a Chief Machine Learning Engineer to lead the vision, strategy, and execution of ML-based systems that intelligently recommend user-generated content while maximizing engagement at scale. You will take ownership of the development, deployment, and optimization of cutting-edge machine learning solutions, driving team excellence in real-time data environments.

Responsibilities

• Set the strategic direction for scalable, high-performance machine learning pipelines across online and offline feature workflows
• Architect and oversee the development of advanced machine learning models, leveraging Python, TensorFlow, and state-of-the-art frameworks
• Lead and optimize the deployment of enterprise-grade inference pipelines for real-time applications such as player telemetry analysis
• Define and enforce standardized machine learning workflows, integrating MLflow and other tools across cross-functional teams
• Build and manage robust data integration pipelines via ETL/ELT processes in enterprise-level environments using Databricks
• Shape the vision for reliable, scalable, and continuously optimized production-grade ML systems across the business
• Develop automated, robust solutions for feature engineering and ensure seamless model deployment across high-complexity systems
• Partner with top stakeholders to align machine learning strategies with large-scale organizational objectives and KPIs
• Champion strategies for efficient dataset management and high-powered computational workflows leveraging Databricks infrastructure
• Drive innovation and enforce enterprise-wide best practices for scalable and highly efficient ML systems

Requirements

• 7+ years of experience designing and deploying scalable machine learning systems in high-complexity environments
• At least 2 years of proven leadership experience in managing ML teams or initiatives
• Extensive expertise with Databricks, MLflow, TensorFlow, and advanced data engineering platforms
• Advanced proficiency in Python, with a strong focus on machine learning, data engineering, and system optimization tasks
• Comprehensive experience with ETL/ELT processes and large-scale data integration pipelines
• Proven track record in optimizing real-time data systems requiring low-latency and high reliability
• Deep expertise in designing and scaling complex online and offline feature engineering workflows at the enterprise level
• Mastery in managing end-to-end ML model lifecycles across high-demand production environments
• Ability to deliver solutions that balance scalability, performance, and maintainability across business-critical applications
• Excellent written and verbal communication skills in English (C1 level or higher)

Nice to have

• Expert-level knowledge of recommender systems for enhancing content discovery and user engagement
• Hands-on experience deploying machine learning infrastructure on AWS, GCP, or equivalent cloud platforms
• Advanced experience with real-time analytics and designing telemetry-driven systems at scale

We offer

• International projects with top brands
• Work with global teams of highly skilled, diverse peers
• Healthcare benefits
• Employee financial programs
• Paid time off and sick leave
• Upskilling, reskilling and certification courses
• Unlimited access to the LinkedIn Learning library and 22,000+ courses
• Global career opportunities
• Volunteer and community involvement opportunities
• EPAM Employee Groups
• Award-winning culture recognized by Glassdoor, Newsweek and LinkedIn