Note: The job is a remote job and is open to candidates in USA. EPAM Systems is looking for a Senior AI Engineer with expertise in Databricks to design, deploy, and maintain scalable machine learning pipelines. The role involves delivering production-ready ML pipelines, monitoring dashboards, and CI/CD pipelines for ML systems.

Responsibilities

• Design, implement and maintain end-to-end ML pipelines on Databricks
• Build workflows for data ingestion, preprocessing, feature engineering, training and inference
• Leverage PySpark, Spark ML and Databricks notebooks/jobs
• Manage model versioning, experiment tracking and reproducibility using MLflow
• Package and deploy models for batch and real-time inference
• Monitor model performance, drift and retraining cycles
• Develop scalable ETL/ELT pipelines using Databricks Delta Lake
• Optimize data storage and access patterns through partitioning, Z-ordering and caching
• Integrate with data sources such as Azure Data Lake, S3, APIs and databases
• Implement CI/CD pipelines for ML workflows using Azure DevOps, GitHub Actions and Databricks Repos and Jobs API
• Configure clusters, autoscaling and cost optimization while applying Infrastructure as Code with Terraform, ARM and Bicep
• Implement logging, alerting and observability to ensure high availability and fault tolerance of ML systems

Skills

• 3+ years of experience in machine learning engineering or related roles
• Expertise in the Databricks platform including workspaces, jobs and clusters
• Proficiency in Apache Spark, PySpark and Python with pandas and scikit-learn
• Skills in MLflow for tracking, registry and deployment
• Competency in CI/CD pipelines, Docker containerization and REST APIs for model serving
• Familiarity with version control using Git
• Background in Azure including Azure Databricks, ADLS, ACR and AML
• Knowledge of data preprocessing, feature engineering and model training and evaluation
• Understanding of libraries such as XGBoost, LightGBM and CatBoost
• English proficiency at B2 level or higher
• Familiarity with AWS including S3, EMR and SageMaker
• Skills in streaming pipelines with Spark Structured Streaming and Databricks Feature Store
• Knowledge of Kubernetes
• Competency in monitoring tools such as Prometheus and Grafana
• Experience with large-scale production systems

Benefits

• Diversity of assignments and projects
• Personal development plan
• Mentoring programs and leadership development
• Certification and professional development support
• Access to learning platforms including more than 2,500 internal courses and the LinkedIn Learning library with 20,000+ courses
• English courses taught by certified teachers
• Extra leave days
• Referral bonuses
• Private health insurance
• Recreation office zones with tea, coffee and snacks
• Sports and game consoles
• IT equipment and Microsoft's Software Assurance Home Use Program (HUP)

Company Overview

Company H1B Sponsorship