AI System Manager

18 hours ago

Gulbarga, Karnataka, India beBeeArtificialIntelligence Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Our company is seeking a skilled and proactive individual to oversee the post-deployment lifecycle of AI/ML systems and solutions.The ideal candidate will have expertise in leading the maintenance, optimization, and performance of deployed AI systems, ensuring continued functionality, reliability, and scalability.Key responsibilities include monitoring & sustenance, performance optimization, stakeholder collaboration, governance & best practices, and incident management.Responsibilities:
  • Monitoring & Sustenance
    • Lead the post-deployment lifecycle of AI solutions, ensuring continued functionality, reliability, and scalability.
    • Establish monitoring frameworks to oversee system performance, usage, and metrics for AI/ML models and APIs.
    • Detect anomalies in AI systems, troubleshoot operational issues, and initiate timely corrective actions.
  • Performance Optimization
    • Continuously assess and optimize the performance of AI models to maintain efficiency and accuracy in production environments.
    • Collaborate with data scientists and engineers to refine algorithms, retrain models, and update solutions as needed.
    • Implement automation where possible to streamline maintenance processes.
  • Stakeholder Collaboration
    • Work with cross-functional teams (engineering, product, operations, etc.) to ensure alignment of AI sustainment activities with business goals.
    • Communicate effectively with stakeholders to provide updates on system health, risks, and improvements.
  • Governance & Best Practices
    • Define and implement best practices for sustaining AI solutions, including documentation, testing protocols, and version control.
    • Ensure compliance with ethical AI standards, regulatory guidelines, and established governance frameworks.
    • Manage and mitigate risks associated with model drift, data shifts, and system vulnerabilities.
  • Incident Management
    • Lead responses to critical incidents involving AI systems by performing root cause analysis and deploying solutions for quick resolution.
    • Advocate for proactive risk prevention and early detection strategies.
    • Mentor and develop junior team members, fostering their skills in AI observability and domain-specific knowledge in ML, Computer Vision, and Generative AI.

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