Skills & Competencies for Principal AI Engineer

Principal AI Engineer job profile

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JOB SUMMARY for Principal AI Engineer

Designs and develops scalable solutions using AI tools and machine-learning models.

JOB RESPONSIBILITIES for Principal AI Engineer

Performs research and testing to develop machine learning algorithms and predictive models. Utilizes big data computation and storage tools to create prototypes and datasets. Conducts model training and evaluation. Integrates, tests, tunes, and monitors solutions. Proficient with multiple AI tools such as Python, Java, or R and machine learning frameworks like Spark, TensorFlow, or sciket-learn.

Principal AI Engineer SALARY RANGE

BASE 50%
$152,817
TOTAL 50%
$165,429
Job Level
P04
Job Code
IT10000585
Education/Degree
Master's Degree or MBA
Reports To
Manager or Head of a Unit/Department

Principal AI Engineer Skills and Competencies List

Proficiency Levels and Behavioural Indicators
Salary.com identifies five increasing levels of proficiency for each skill/competency. Some jobs require only a relatively low level of proficiency in each skill/competency, while other jobs will require a more advanced level of proficiency in the same skill/competency. These levels rate the degree of proficiency (skill level, expertise) we expect the incumbent to perform in the given skill/competency for the given job. Note that we intentionally do not associate timeframes or years of experience in performing the skill/competency because that can be misleading. Proficiency levels identify what the incumbent knows and can do rather than how long they have been doing it. Also, note that the proficiency levels are cumulative, e.g., a level 4 proficiency implies the ability to perform all the behaviors at the lower levels.
Check each Principal AI Engineer skill and competencie below to view definitions.
INDUSTRY COMPETENCIES JOB FAMILY COMPETENCIES CORE COMPETENCIES
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8 hard skills or competencies (industry competencies) for Principal AI Engineer

1 Industry Competency – Software Engineering
Proficiency Level -4
Skill definition-Applying computer science and engineering principles, methods, and practices to design, develop, deploy, and maintain reliable software systems.
Level 1 Behaviors
(General Familiarity)
Explains the step-by-step procedures for developing new and enhanced software products.
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Level 2 Behaviors
(Light Experience)
Uses specific programming languages and platforms to write code and create software programs.
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Level 3 Behaviors
(Moderate Experience)
Works collaboratively with development teams to correct complex errors in software codes.
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Level 4 Behaviors
(Extensive Experience)
Trains teams on developing highly responsive user interfaces (UI) to enhance customer experience.
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Level 5 Behaviors
(Mastery)
Keeps abreast of the latest industry coding best practices to maximize application readability and performance.
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2 Industry Competency – Artificial Intelligence (AI)
Proficiency Level -4
Skill definition-Applying the technologies and methodologies of artificial intelligence(AI) to develop and implement AI products and services for various business goals.
Level 1 Behaviors
(General Familiarity)
Lists the key AI components, such as machine learning and natural language processing.
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Level 2 Behaviors
(Light Experience)
Supports the development of sophisticated models using structured and unstructured data sets for analysis.
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Level 3 Behaviors
(Moderate Experience)
Translates unstructured data into useful information by auto-tagging images and text-to-speech conversions.
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Level 4 Behaviors
(Extensive Experience)
Manages AI teams to develop and test prototype software to implement innovative algorithms.
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Level 5 Behaviors
(Mastery)
Formulates standard methodologies for machine learning and AI product development and solutions.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

5 general skills or competencies (Job family competencies) for Principal AI Engineer

1 Job Family Competencies – Cloud Computing
Proficiency Level -3
Skill definition-Providing on-demand computing services that allow users to store, manage, and process their data remotely.
Level 1 Behaviors
(General Familiarity)
Explains the automation and orchestration frameworks of cloud computing.
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Level 2 Behaviors
(Light Experience)
Follows our established procedures in helping with the planning of cloud computing strategies.
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Level 3 Behaviors
(Moderate Experience)
Maintains multi-site network connectivity to ensure the availability of cloud computing resources.
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Level 4 Behaviors
(Extensive Experience)
Monitors industry trends to enhance the future direction of cloud services in our organization.
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Level 5 Behaviors
(Mastery)
Designs and develops tools to support overall cloud computing capabilities at our organization.
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2 Job Family Competencies – Deep Learning
Proficiency Level -4
Skill definition-Analyzing, developing, and applying big data and algorithms to imitate how humans think and learn.
Level 1 Behaviors
(General Familiarity)
Explains the application of deep learning algorithms and workflows.
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Level 2 Behaviors
(Light Experience)
Performs data analysis using specialized software and deep machine learning methods.
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Level 3 Behaviors
(Moderate Experience)
Performs forward propagation and backpropagation to reduce the error and achieve high accuracy in a particular task.
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Level 4 Behaviors
(Extensive Experience)
Facilitates testing of deep learning models to identify and resolve engineering design problems.
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Level 5 Behaviors
(Mastery)
Generates a mathematical framework to integrate deep learning algorithms into formal control methods.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

9 soft skills or competencies (core competencies) for Principal AI Engineer

1 Core Competencies – Innovation
Proficiency Level -4
Skill definition-The ability and process of implementing new ideas and initiatives to improve organizational performance.
Level 1 Behaviors
(General Familiarity)
Explains our key business strategies and priorities.
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Level 2 Behaviors
(Light Experience)
Reports and communicates market and competitor status regularly to the management team.
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Level 3 Behaviors
(Moderate Experience)
Evaluates supply chain efficiency with an eye toward improving shortcomings.
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Level 4 Behaviors
(Extensive Experience)
Leverages the latest technologies and tools that enhance business analytics.
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Level 5 Behaviors
(Mastery)
Designs and implements feedback loops to identify and promptly address business problems.
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2 Core Competencies – Attention to Detail
Proficiency Level -4
Skill definition-Executing and completing a task with a high level of accuracy.
Level 1 Behaviors
(General Familiarity)
Lists best practices and tools to maintain high accuracy and thoroughness in the workplace.
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Level 2 Behaviors
(Light Experience)
Records all appointments on the calendar to easily track daily activities.
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Level 3 Behaviors
(Moderate Experience)
Sets up processes to ensure delivery of high-quality work.
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Level 4 Behaviors
(Extensive Experience)
Employs techniques for motivating personnel to meet or exceed accuracy goals.
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Level 5 Behaviors
(Mastery)
Leads the creation of tools for enhancing and assuring accuracy.
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3 Principal AI Engineer - Skill and Competency
Proficiency Level - 3
4 Skill and Competency - Principal AI Engineer
Proficiency Level - 4
5 Competency for - Principal AI Engineer
Proficiency Level - 5

Summary of Principal AI Engineer skills and competencies

There are 8 hard skills for Principal AI Engineer, Software Engineering, Artificial Intelligence (AI), Cognitive Computing, etc.
5 general skills for Principal AI Engineer, Cloud Computing, Deep Learning, Machine Learning, etc.
9 soft skills for Principal AI Engineer, Innovation, Attention to Detail, Time Management, etc.
While the list totals 22 distinct skills, it's important to note that not all are required to be mastered to the same degree. Some skills may only need a basic understanding, whereas others demand a higher level of expertise.
For instance, as a Principal AI Engineer, he or she needs to be skilled in Innovation, be skilled in Attention to Detail, and be skilled in Time Management.

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