Chief Machine Learning Engineer

hace 2 días

Remote, Perú EPAM Systems, Inc. A tiempo completo

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
- 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
- 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

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