Designs and develops scalable solutions using AI tools and machine-learning models.
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.
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 AI Engineer V skill and competencie below to view definitions.
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.
Level 2 Behaviors
(Light Experience)
Prepares engineering documentation to ensure software adheres to user expectations.
Level 3 Behaviors
(Moderate Experience)
Utilizes version control systems (VCS) to track and manage changes in software codes.
Level 4 Behaviors
(Extensive Experience)
Evaluates and modifies existing development processes to optimize software production and reduce errors.
Level 5 Behaviors
(Mastery)
Develops optimization strategies to improve software product quality and usability.
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.
Level 2 Behaviors
(Light Experience)
Selects appropriate programming languages in building, testing, and deploying AI models.
Level 3 Behaviors
(Moderate Experience)
Translates unstructured data into useful information by auto-tagging images and text-to-speech conversions.
Level 4 Behaviors
(Extensive Experience)
Manages AI teams to develop and test prototype software to implement innovative algorithms.
Level 5 Behaviors
(Mastery)
Formulates standard methodologies for machine learning and AI product development and solutions.
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 common design patterns, data structures, and algorithms in cloud computing.
Level 2 Behaviors
(Light Experience)
Follows our established procedures in helping with the planning of cloud computing strategies.
Level 3 Behaviors
(Moderate Experience)
Uses modern cloud computing services to improve the performance of cloud applications.
Level 4 Behaviors
(Extensive Experience)
Monitors industry trends to enhance the future direction of cloud services in our organization.
Level 5 Behaviors
(Mastery)
Designs and develops tools to support overall cloud computing capabilities at our organization.
Skill definition-Designing and utilizing digital systems to process, analyze, and interpret visual data.
Level 1 Behaviors
(General Familiarity)
Explains the use of convolutional neural networks in building computer vision models.
Level 2 Behaviors
(Light Experience)
Supports the assessment of annotated data for computer vision applications.
Level 3 Behaviors
(Moderate Experience)
Utilizes computer vision algorithms to analyze complex visual data.
Level 4 Behaviors
(Extensive Experience)
Evaluates new algorithms to detect issues in computer vision models.
Level 5 Behaviors
(Mastery)
Establishes best practices, processes, and standards in developing computer vision solutions.
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.
Level 2 Behaviors
(Light Experience)
Reports and communicates market and competitor status regularly to the management team.
Level 3 Behaviors
(Moderate Experience)
Implements effective marketing strategies that achieve improved business outcomes.
Level 4 Behaviors
(Extensive Experience)
Optimizes business processes based on deep insight into various business unit functions.
Level 5 Behaviors
(Mastery)
Evaluates industry and market trends to identify new business opportunities.
Skill definition-Managing and setting priorities, goals, and timetables to boost productivity and efficiency in completing tasks.
Level 1 Behaviors
(General Familiarity)
Explains the importance of time management in driving the overall productivity of our business.
Level 2 Behaviors
(Light Experience)
Follows an updated calendar to list and complete tasks and assignments according to priority level.
Level 3 Behaviors
(Moderate Experience)
Utilizes departmental tools and best practices to organize tasks effectively and productively.
Level 4 Behaviors
(Extensive Experience)
Manages teams in streamlining work-related tasks to prioritize highest value tasks firsts.
Level 5 Behaviors
(Mastery)
Leads transformational changes to work plans to drive the proper utilization of time and resources.
There are 8 hard skills for AI Engineer V, Software Engineering, Artificial Intelligence (AI), Cognitive Computing, etc.
6 general skills for AI Engineer V, Cloud Computing, Computer Vision, Deep Learning, etc.
8 soft skills for AI Engineer V, Innovation, Time Management, Problem Solving, 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 an AI Engineer V, he or she needs to be skilled in Innovation, be skilled in Time Management, and be skilled in Problem Solving.
