2 weeks ago Be among the first 25 applicants
Get AI-powered advice on this job and more exclusive features.
EPAM is a leading global provider of digital platform engineering and development services.
We are committed to having a positive impact on our customers, our employees, and our communities.
We embrace a dynamic and inclusive culture.
Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow.
No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
We are in search of a Lead Machine Learning Engineer to direct the design, implementation, and optimization of ML-based systems that intelligently recommend user-generated content, aiming to boost engagement.
This role involves leading the development of robust machine learning pipelines and overseeing high-performance deployments suited for real-time data environments.
Responsibilities
- Lead the design and execution of scalable, high-performance machine learning pipelines for online and offline feature engineering
- Drive the development and tuning of advanced machine learning models, primarily utilizing Python and TensorFlow
- Optimize and manage the deployment of inference pipelines tailored for real-time, low-latency applications such as player telemetry
- Guide and standardize machine learning workflow management processes using MLflow across the team
- Supervise and expand data integration pipelines via ETL/ELT processes on Databricks
- Ensure reliability, debugging, and continuous performance tuning of production-grade ML systems
- Establish scalable and automated methodologies for feature engineering and durable model deployments
- Collaborate effectively with senior stakeholders to align machine learning solutions with organizational objectives
- Strategize effective utilization of Databricks for efficient dataset management and computational workflows
- Set and uphold industry-leading best practices for scalable, maintainable, and efficient ML systems
Requirements
- 5+ years of experience building scalable machine learning pipelines and production-grade workflows
- Minimum of 1 year of leadership experience in relevant roles
- Demonstrated expertise in Databricks, MLflow, and TensorFlow in professional applications
- Strong proficiency in Python for advanced machine learning and data engineering
- Solid background in ETL/ELT platforms with significant experience in large-scale integration processes
- Deep familiarity with real-time processing systems optimized for low latency
- Proven skills in designing and scaling workflows for both online and offline feature engineering
- Expertise in managing ML model lifecycles and optimizing pipelines
- Capability to deliver scalable, high-performance solutions in multifaceted and evolving environments
- Excellent command of written and spoken English (B2+ level)
Nice to have
- Comprehensive understanding of recommender systems with an emphasis on enhancing content discoverability and engagement
- Proficiency in deploying machine learning systems within AWS or comparable cloud infrastructure
- Background in real-time analytics coupled with telemetry-driven data solutions
We offer
- International projects with top brands
- Work with global teams of highly skilled, diverse peers
- 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
#J-18808-Ljbffr