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AI DevOps / SRE Engineer

AI DevOps / SRE Engineer

EpamTurkiye
30+ gün önce
İş tanımı

Description

As an AI DevOps / SRE Engineer, you will be pivotal in deploying, maintaining, and scaling our AI solutions, including LLMs and RAG systems. You will work closely with data scientists and software developers to ensure seamless integration and operational efficiency of our AI deployments. Your role will involve both classic DevOps tasks and innovative approaches to MLOps, ensuring high availability and optimal performance of our systems.

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Responsibilities

  • Implement and maintain CI / CD pipelines for AI and machine learning projects, ensuring robust deployment strategies and continuous integration
  • Monitor and ensure the reliability, availability, and performance of AI applications, particularly those involving LLMs and RAG
  • Collaborate with AI research teams to operationalize machine learning models and systems efficiently
  • Develop and enforce best practices for version control, configuration management, and testing of AI-driven software solutions
  • Utilize MLOps tools such as Kubeflow, MLflow, or TensorFlow Extended (TFX) to streamline the machine learning lifecycle from experimentation to production
  • Implement monitoring solutions that track both system metrics and model performance to facilitate proactive issue resolution
  • Participate in on-call rotations to support the operational health of critical systems, employing SRE principles to meet service-level objectives (SLOs) and reduce downtime

Requirements

  • Bachelors degree in Computer Science, Engineering, or a related field
  • Proven experience as a DevOps Engineer or SRE, with a strong background in software development and automation
  • Experience with deployment and management of LLMs, including technologies like RAG
  • Proficient in CI / CD tools (e.g., Jenkins, GitLab CI, CircleCI) and infrastructure as code (e.g., Terraform, Ansible)
  • Knowledge of container orchestration technologies (e.g., Kubernetes, Docker)
  • Familiarity with MLOps tools and practices to support machine learning lifecycle management
  • Strong problem-solving skills and ability to work in a dynamic, fast-paced environment
  • Nice to have

  • Experience with cloud services (AWS, GCP, Azure) particularly in AI / ML deployments
  • Background in monitoring tools like Prometheus, Grafana, and ELK stack
  • Knowledge of Python, particularly in data science and machine learning contexts
  • Certification in Kubernetes, AWS / GCP / Azure, or similar technologies
  • We offer

  • CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT : Diversity of tasks and projects Assessment center for objective review of competency level Personal development plan Mentoring programs and leadership development Certification and professional development support Access to learning platforms including more than 2, internal courses and the LinkedIn Learning library with 20,+ courses English courses taught by certified teachers
  • CORPORATE BENEFITS : Extra leave days Referral bonuses
  • COMPENSATION PACKAGE : Competitive compensation paid in USD Regular salary and performance reviews
  • MEDICAL & HEALTHCARE : Private health insurance Well-being events
  • WORKING ENVIRONMENT : Recreation areas and kitchens Tea, coffee, and snacks Well-being events Sports equipment and game consoles IT Equipment Microsoft's Software Assurance Home Use Program (HUP)
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