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Job Description

Overview:

We are looking for an experienced DevOps Engineer with 2+ years of experience to join our innovative AI team. In this role, you will be the bridge between our AI/ML development and IT operations, responsible for building and managing the infrastructure that powers our AI products. You will play a critical part in automating and streamlining the entire machine learning lifecycle, from development to deployment and monitoring. This position requires a strong background in DevOps practices and a keen interest in the unique challenges of deploying and scaling AI and machine learning systems.

Responsibilities:

  • CI/CD for AI: Design, implement, and maintain robust CI/CD pipelines for the automated testing, integration, and deployment of our AI applications and machine learning models.
  • Infrastructure as Code (IaC): Use tools like Terraform to define, deploy, and manage our cloud infrastructure on AWS, ensuring a reproducible and scalable environment for our AI workloads.
  • Containerization and Orchestration: Deploy, manage, and scale our AI services and models using Docker and Kubernetes, ensuring high availability and efficient resource utilization.
  • Monitoring and Observability: Implement comprehensive monitoring and logging solutions to track the performance and health of our backend services and AI models in production, enabling quick identification and resolution of issues.
  • Automation: Develop scripts and tools, primarily in Python or Rust, to automate infrastructure management, deployment processes, and other operational tasks.
  • Collaboration: Work closely with our AI/ML engineers and developers to optimize our deployment strategies, improve our DevOps practices, and ensure the reliability and scalability of our AI systems.
  • MLOps: Champion and implement MLOps best practices, including model versioning, automated retraining pipelines, and governance to ensure the reproducibility and reliability of our machine learning models.

Requirements:

  • 2+ years of hands-on experience in a DevOps or Site Reliability Engineering (SRE) role.
  • Strong proficiency with containerization and orchestration technologies, specifically Docker and Kubernetes.
  • Proven experience with CI/CD tools such as Jenkins, GitHub Actions, or similar.
  • Solid experience with infrastructure as code (IaC) tools, with a preference for Terraform.
  • Proficiency in Linux and scripting languages, with a strong preference for Python.
  • A solid understanding of monitoring and logging tools and best practices.
  • Excellent troubleshooting and problem-solving skills, with a passion for automation.
  • Strong communication and collaboration skills, with a team-oriented mindset.

Preferred Qualifications:

  • Direct experience with the deployment and operationalization of machine learning models (model serving).
  • Familiarity with the operational aspects of data infrastructure, including Kafka, Redis, and PostgreSQL.
  • An interest in or experience with modern programming languages like Rust or Elixir for systems-level tooling.
  • A strong understanding of security best practices as they apply to AI and cloud infrastructure.

Job Type: Contractual / Temporary

Pay: ₹840,000.00 - ₹960,000.00 per year

Ability to commute/relocate:

  • Narhe, Pune, Maharashtra: Reliably commute or planning to relocate before starting work (Required)

Application Question(s):

  • Will you be available for face to face interview?

Experience:

  • CI/CD: 2 years (Required)

Work Location: In person

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