We are seeking a Senior Machine Learning Engineer to join our team and contribute to the GenAI project.
In this role, you will focus on designing, building, and optimizing backend systems that support LLM-driven applications using OpenAI APIs. You will leverage your expertise in MLOps, CI/CD, observability, and cloud-native technologies to ensure the scalability, reliability, and performance of AI-powered solutions.
Responsibilities
- Develop and optimize backend services for AI and LLM-based applications
- Integrate and manage LLM-based applications in cloud environments
- Scale AI applications to meet performance and reliability requirements
- Implement CI/CD pipelines to automate deployment processes
- Monitor AI services to ensure performance and reliability
- Establish observability and logging for tracking LLM API performance
- Collaborate with DevOps teams to streamline workflows and improve system uptime
- Work closely with AI and Data Science teams to enhance application functionality
- Leverage cloud platforms, with a preference for Azure, to host and scale AI solutions
- Design and develop APIs and microservices to enable AI-powered features
Requirements
- At least 3 years of experience in Machine Learning Engineering with a focus on software and backend systems
- Strong expertise in integrating and working with OpenAI APIs and AI services
- Proficiency in MLOps tools such as Orion, ArgoCD, and Opsera for deployment automation
- Hands-on experience with monitoring and observability tools like Grafana, Dynatrace, and ThoughtSpot
- Deep understanding of cloud platforms, particularly Azure, as well as Apache Spark and Databricks
- Strong Python programming skills for backend development
- Experience in designing and implementing APIs and microservices architecture
- Fluent English communication skills, both written and spoken, at a B2+ level or higher
Nice to have
- Knowledge of Data Science principles and techniques
- Experience working with Large Language Models (LLMs)
- Familiarity with Natural Language Processing (NLP) concepts 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