Lead/Senior Domino Data Lab with Python

We are seeking an experienced Lead/Senior Domino Data Lab Engineer with strong Python expertise to design, develop, and deploy scalable data science applications and machine learning solutions. In this role, you will leverage the Domino Data Lab platform to build production-ready models, collaborate with cross-functional teams, and drive best practices across the ML lifecycle.

Responsibilities

• Design, develop, and deploy applications and machine learning models on the Domino Data Lab platform
• Build and maintain Python-based solutions using modern frameworks and libraries
• Develop REST APIs to expose models and services for enterprise consumption
• Manage Domino Projects, Workspaces, Jobs, and Environments to support data science workflows
• Implement MLOps practices covering model deployment, monitoring, and productionization
• Collaborate with data scientists, engineers, and stakeholders to translate business needs into technical solutions
• Integrate applications with various databases and data sources
• Establish CI/CD pipelines and containerization strategies for reliable delivery
• Mentor junior team members and promote software development best practices
• Ensure the reliability, scalability, and performance of deployed models and services

Requirements

• 5-14 years of professional software/data engineering experience
• Strong hands-on expertise in Domino Data Lab, including Projects, Workspaces, Jobs, and Environments
• Proficiency in Python development and scripting
• Skills in Pandas, NumPy, and Scikit-learn or similar Python libraries
• Experience developing REST APIs with FastAPI, Flask, or Django
• Understanding of MLOps principles and the end-to-end ML model lifecycle
• Knowledge of Git, Docker, and CI/CD workflows
• Familiarity with cloud platforms such as AWS, Azure, or GCP
• Background in model deployment, monitoring, and productionization
• Capability to work with databases and data integration solutions
• Understanding of software development best practices

Nice to have

• Experience with Node.js
• Familiarity with Kubernetes for orchestration
• Exposure to MLOps or Machine Learning platform tooling
• Background in Jupyter or similar Data Science environments
• Experience with enterprise application integration

Benefits

Opportunity to work on technical challenges that may impact across geographies

Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications

Opportunity to share your ideas on international platforms

Sponsored Tech Talks & Hackathons

Unlimited access to LinkedIn learning solutions

Possibility to relocate to any EPAM office for short and long-term projects

Focused individual development

Benefit package:

• Health benefits
• Retirement benefits
• Paid time off
• Flexible benefits

Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)