Live opening · Posted 2 days ago
At a glance
The key details from the original listing.
About the role
Description supplied by the original job listing.
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 looking for a Senior AI Engineer to own the end-to-end lifecycle of machine learning systems, from problem formulation to production deployment. You will design scalable ML architectures, build robust pipelines, and collaborate across teams to deliver impactful AI-driven solutions.
Responsibilities
Own end-to-end lifecycle of ML systems: problem formulation, data collection, feature engineering, model training, evaluation, deployment, and monitoring
Design and implement scalable ML architectures including batch and real-time pipelines
Work with large-scale structured and unstructured datasets such as clickstream, transactional, text, and image data
Develop and deploy models such as recommendation systems, ranking models, forecasting models, and classification/regression systems
Apply deep learning techniques including neural networks, transformers, and representation learning where appropriate
Build and maintain feature stores, model registries, and experiment tracking systems
Ensure production readiness through latency optimization, scalability, reliability, and cost efficiency
Collaborate with engineering, product, and business teams to define KPIs and success metrics
Requirements
3+ years of experience in machine learning engineering or a related field
Expertise in MLOps practices for managing the ML lifecycle
Proficiency in PySpark and Python for building scalable data and ML pipelines
Background in designing and deploying production-grade ML systems
Understanding of batch and real-time data processing architectures
Experience working with large-scale structured and unstructured datasets
English proficiency at B2 level or higher
Nice to have
Familiarity with Apache Kafka and MLflow
Knowledge of Machine Learning and PyTorch
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
EPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.
Work arrangement
Yes
Your early-applicant advantage
Live timing from JobBeeper.
More openings worth a look
Recently tracked roles with full details and direct application links.