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 importance of using suitable programming languages and platforms in software engineering.
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Level 2 Behaviors
(Light Experience)
Prepares engineering documentation to ensure software adheres to user expectations.
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Level 3 Behaviors
(Moderate Experience)
Utilizes version control systems (VCS) to track and manage changes in software codes.
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Level 4 Behaviors
(Extensive Experience)
Evaluates and modifies existing development processes to optimize software production and reduce errors.
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Level 5 Behaviors
(Mastery)
Develops optimization strategies to improve software product quality and usability.
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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)
Identifies evolving trends and key challenges in AI applied machine learning and deep learning.
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Level 2 Behaviors
(Light Experience)
Selects appropriate programming languages in building, testing, and deploying AI models.
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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)
Cites examples of public cloud computing architectures and services.
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Level 2 Behaviors
(Light Experience)
Assists in developing automated solutions using cloud-based server-less computing platforms.
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Level 3 Behaviors
(Moderate Experience)
Analyzes various applications and platforms to automate and orchestrate cloud computing activities.
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Level 4 Behaviors
(Extensive Experience)
Consults on emerging cloud computing technologies to improve our operational efficiency.
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Level 5 Behaviors
(Mastery)
Builds security programs to elevate our security posture within a cloud computing infrastructure.
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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)
Cites examples of state-of-the-art methodologies and software libraries in the field of deep learning.
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Level 2 Behaviors
(Light Experience)
Assists in implementing and optimizing new vision algorithms for deep learning.
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Level 3 Behaviors
(Moderate Experience)
Analyzes relevant information from large amounts of data to automate and optimize deep learning processes.
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Level 4 Behaviors
(Extensive Experience)
Collaborates with the team to communicate deep learning concepts, technologies, and solutions to prospective clients.
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Level 5 Behaviors
(Mastery)
Builds scalable and usable deep learning tools to improve system performance and mobility safety.
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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)
Describes how our business makes money and our key business objectives.
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Level 2 Behaviors
(Light Experience)
Assists in designing business models and operating plans.
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Level 3 Behaviors
(Moderate Experience)
Analyses the business impact of demographic changes; suggests effective responses.
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Level 4 Behaviors
(Extensive Experience)
Consults on the selection and adjustment of the go-to-market strategy.
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Level 5 Behaviors
(Mastery)
Builds a conceptual model to ensure a continuous increase of business sense within our business.
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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)
Cites steps and tips to improve attention to detail in the workplace.
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Level 2 Behaviors
(Light Experience)
Keeps full attention when listening to understand the message.
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Level 3 Behaviors
(Moderate Experience)
Balances between accuracy and efficiency for different tasks or programs.
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Level 4 Behaviors
(Extensive Experience)
Creates and implements quality management processes for our business.
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Level 5 Behaviors
(Mastery)
Defines possible hurdles to projects and creates strategies to deal with them.
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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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