Manager Artificial Intelligence Job Description (Word Format)

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Order Manager Blockchain Job DescriptionThe Manager Artificial Intelligence is responsible for the overall management and direction of all technical services functions associated with Artificial Intelligence (AI) and Machine Learning (ML) applications.  The manager works within the Information Technology arena.

The Manager AI provides the strategic direction on compliance for the design, development, and implementation of AI models into operational workflows, including helping draft and review the procedures that support a compliance system. Additional responsibilities may include guiding AI teams with project planning, system architecture, risk management, verification & validation, and continuous monitoring.

The Manager AI consults with multiple stakeholders to help guide the enterprise’s best practices, including data quality, good machine learning practices, and monitoring the effectiveness of AI models throughout their life cycle. A multidisciplinary approach that unifies key stakeholders and subject matter experts is a driver of the Manager AI role and responsibilities.

The job description for the Manager Artificial Intelligence spells out the challengers, duties and priorities for the position. This document also defines the career path and where the Manager Artificial Intelligence falls in the reporting structure . The Job description defines the the role’s problems/challenges, essential position functions, accountabilities, authority, contact points, position requirements, which could include certifications, skills, experience, and education, and career ladder.

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Core of Job Description - KPI Metrics for Artificial Intelligence

KPIs are established to measure data quality or security. Other commonly used KPIs for AI include:

  • Mean time to repair (MTTR). Measures the duration of error repair in an AI.
  • Mean absolute error (MAE). Determines the average difference of predictions made by a regression model to the true value.
  • First contact resolution rate (FCRR). Reveals the percentage of problems solved via basic support.
  • True or false positive rate (T/FPR). A measure of fairness that helps determine the sensitivity and specificity of predicted classifications.

Salary Manager AI

The Manager of Artificial Intelligence and Machine Learning is one of the hardest positions to fill today. Based on our Salary Survey data the national median salary is $144,100. The overall salary range is between $96,500 to $279,000.

Manager AI Salary

Manager AI Position Requirements

The Manager AI helps implement infrastructure that advances the strategy for AI and ML across the enterprise. The Manager AI is a thought leader on the application of AI in the enterprise’s industry, with an initial focus on guiding engineering processes for the safe, effective, and ethical implementation of AI and ML.

Order Chief Digital Officer Job Description digital marketingThe Manager Artificial Intelligence is responsible for all AI applications, systems software, and hardware implementations including data communications for the enterprise’s AI applications. The manager must strive to ensure the continued operational success of these areas through well-monitored AI applications, equipment, and software. As such, the manager is extremely important to the enterprise's current and future business operations.

Position requirements include:

  • Diverse technical experience, including AI model development, software engineering, regulated software quality and risk management, and monitoring of deployed software.
  • Experience with data modeling and data exploration tools, including expertise in the use of scientific computing and data management packages is required.
  • A demonstrated ability to provide vision and strategic direction at an institutional or enterprise level.
  • Exceptional human relations and communication (written, verbal, and listening) skills will be necessary to effectively communicate across disciplines and stakeholders.
  • Understand working in a compliance based and regulated environment, including building, deploying, and supporting secure software throughout the AI development life cycle.
  • Experience with quality systems regulation is required. Additional experience with applicable ISO standards.

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