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 Lead MLOps Gen AI Engineer to support the development and deployment of AI tools.
This role bridges data science, engineering, and cloud infrastructure, focusing on building scalable and automated production-grade AI systems. You will work closely with data scientists, business stakeholders, and cloud engineers to convert prototypes into dependable, high-performance applications that drive predictive analytics, generative AI solutions, and interactive dashboards for business leaders. If you have substantial experience in MLOps and cloud infrastructure and enjoy collaborating across teams, we encourage you to apply.
Responsibilities
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Collaborate with data scientists to convert ML and generative AI experiments into scalable production pipelines
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Develop and maintain shared code repositories and reusable components
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Design and implement CI/CD pipelines in AWS or Azure environments for deploying models, APIs, and generative AI tools
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Build and manage data pipelines and DataOps processes
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Containerize applications using Docker and deploy them with cloud-native services
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Automate infrastructure provisioning using Terraform and manage database schemas in Azure and Snowflake
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Deploy and administer generative AI applications such as chatbots, retrieval-augmented generation (RAG) systems, and predictive tools
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Implement monitoring, observability, and explainability solutions to ensure system stability and performance
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Establish alerting, rollback strategies, and observability frameworks to maintain operational stability
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Participate in code reviews and recommend improvements to workflows and processes
Requirements
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Experience of 8 to 12 years in MLOps or DevOps engineering
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Proven leadership experience in managing AI or ML deployment projects
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Background in collaborating with data scientists and cloud engineers
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Expertise in building CI/CD pipelines in AWS or Azure platforms
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Skills in containerization using Docker and deploying applications in cloud environments
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Proficiency in infrastructure automation using Terraform
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Knowledge of managing data schemas in cloud data warehouses such as Azure and Snowflake
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Understanding of generative AI fundamentals and applications
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Capability to deploy and manage AI models and APIs in production
Nice to have
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Familiarity with large language models (LLM)
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Experience with retrieval-augmented generation (RAG) systems
We offer
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Opportunity to work on technical challenges that may impact across geographies
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Vast opportunities for self-development: online university, knowledge sharing opportunities globally, learning opportunities through external certifications
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Opportunity to share your ideas on international platforms
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Sponsored Tech Talks & Hackathons
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Unlimited access to LinkedIn learning solutions
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Possibility to relocate to any EPAM office for short and long-term projects
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Focused individual development
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Benefit package:
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Health benefits
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Retirement benefits
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Paid time off
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Flexible benefits
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Forums to explore beyond work passion (CSR, photography, painting, sports, etc.)