AI Ops Engineer

The AI Ops Engineer manages thedeployment, monitoring, and maintenance of AI models. This role involvesensuring the reliability, scalability, and performance of AI systems,collaborating with cross-functional teams to optimize AI operations, and troubleshootingissues as they arise.

Responsibilities and Duties

• Deploy,monitor, and maintain AI models and systems to ensure optimal performance andreliability.
• Implementand manage CI/CD pipelines for the continuous integration and delivery of AImodels.
• Collaboratewith data scientists, AI engineers, and other stakeholders to understand modelrequirements and ensure successful deployment.
• Monitorthe performance of AI models and systems, identifying and resolving issuespromptly.
• Developand maintain automated monitoring and alerting systems to ensure the health andperformance of AI systems.
• OptimizeAI models and infrastructure for scalability and efficiency
• Ensurecompliance with data governance, security, and regulatory standards in AIoperations.
• Documentdeployment procedures, monitoring processes, and maintenance activities.
• Stayupdated with the latest advancements in AI operations and infrastructuretechnologies.
• Providetechnical support and guidance to junior team members.
• Participatein project planning and contribute to the development of project timelines anddeliverables.
• Performother duties relevant to the job as assigned by the Sr. AI Ops Engineer orsenior management.

Requirements

• Bachelor’sdegree in Computer Science, Information Technology, or a related field
• Relevantcertifications (e.g., AWS Certified DevOps Engineer, Google Cloud ProfessionalDevOps Engineer) are preferred
• Minimumof 3 years of experience in AI operations, DevOps, or related fields
• Experiencein managing the deployment and maintenance of AI models
• Strongprogramming skills in languages such as Python
• Proficiency in AI and machinelearning frameworks (e.g., TensorFlow, PyTorch)
• Experience with CI/CD tools (e.g.,Jenkins, GitLab CI)
• Excellent problem-solving andtroubleshooting skills
• Strongcommunication and interpersonal skills
• In-depthknowledge of AI operations and infrastructure management
• Familiarity with cloud platforms(e.g., AWS, Azure, Google Cloud) and their AI services
• Understandingof data governance, security, and regulatory standards
• Ability tomanage multiple tasks and prioritize effectively
• Strong attention to detail andcommitment to delivering high-quality work
• Abilityto work independently and as part of a team
• Programminglanguages (e.g., Python)
• AI and machine learning frameworks(e.g., TensorFlow, PyTorch)
• CI/CD tools (e.g., Jenkins, GitLabCI)
• Monitoring and logging tools (e.g.,Prometheus, ELK Stack)
• Collaborationand communication tools (e.g., Slack, Microsoft Teams)
  

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