We are seeking a Machine Learning Engineer to join our team and support the GenAI initiative. In this role, you will focus on designing, improving, and optimizing backend infrastructure to power LLM-based applications using OpenAI APIs. Your skills in MLOps, CI/CD, observability, and cloud-native technologies will be essential to ensure the reliability, scalability, and efficiency of AI-driven systems.

Responsibilities

• Develop and improve backend infrastructure for AI and LLM-based solutions
• Integrate and oversee LLM applications within cloud environments
• Scale AI systems to meet performance and reliability requirements
• Implement automated deployment processes through CI/CD pipelines
• Track and maintain the performance of AI services to ensure consistency
• Establish logging and observability frameworks for monitoring LLM API performance
• Collaborate with DevOps teams to streamline workflows and enhance system dependability
• Work closely with AI and Data Science teams to develop and enhance application features
• Leverage cloud platforms, especially Azure, to deploy and scale AI-powered applications
• Design and build APIs and microservices to support AI-driven functionalities

Requirements

• At least 2 years of experience in Machine Learning Engineering with a focus on backend and software development
• Strong expertise in integrating and working with OpenAI APIs and other AI services
• Hands-on experience with MLOps tools such as Orion, ArgoCD, and Opsera for deployment automation
• Proficiency with monitoring and observability tools, including Grafana, Dynatrace, and ThoughtSpot
• Comprehensive knowledge of cloud platforms, particularly Azure, as well as Apache Spark and Databricks
• Advanced Python programming skills for backend development and implementation
• Proven experience in designing and building APIs and microservices architecture
• Fluency in English, both verbal and written, with a minimum proficiency level of B2+

Nice to have

• Knowledge of Data Science principles and workflows
• Experience with Large Language Models (LLMs)
• Understanding of Natural Language Processing (NLP) methodologies and applications

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