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)
Defines the concepts, components, and methodologies used in software engineering.
Level 2 Behaviors
(Light Experience)
Follows established guidelines and standards when carrying out basic software maintenance tasks.
Level 3 Behaviors
(Moderate Experience)
Operates complex quality assurance tools to test and evaluate software products before deployment.
Level 4 Behaviors
(Extensive Experience)
Directs the implementation of testing procedures to improve the usability of software products.
Level 5 Behaviors
(Mastery)
Designs and builds news software engineering tools to drive efficiency in operations.
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)
Describes the importance and goals of artificial intelligence (AI) across businesses and organizations.
Level 2 Behaviors
(Light Experience)
Compiles reports and assessments on data and AI capability requirements for senior management's review.
Level 3 Behaviors
(Moderate Experience)
Consults with managers to determine and refine machine learning objectives.
Level 4 Behaviors
(Extensive Experience)
Evaluates advanced statistical techniques using AI methods to advance knowledge and pursue new approaches.
Level 5 Behaviors
(Mastery)
Creates machine learning algorithms to analyze vast volumes of historical data to make predictions.
Skill definition-Providing on-demand computing services that allow users to store, manage, and process their data remotely.
Level 1 Behaviors
(General Familiarity)
Cites security solutions for cloud-based computing.
Level 2 Behaviors
(Light Experience)
Assists with transitioning cloud computing databases and software as a service technology.
Level 3 Behaviors
(Moderate Experience)
Completes the architecture assessments of new computing solutions within public cloud services.
Level 4 Behaviors
(Extensive Experience)
Evaluates cloud computing architectures to drive cost reduction in managing IT systems.
Level 5 Behaviors
(Mastery)
Conceptualizes new IT cloud computing products and service offerings to drive business continuity.
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)
Develops and executes strategies to optimize analytics from computer vision algorithms.
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)
Evaluates supply chain efficiency with an eye toward improving shortcomings.
Level 4 Behaviors
(Extensive Experience)
Leverages the latest technologies and tools that enhance business analytics.
Level 5 Behaviors
(Mastery)
Designs and implements feedback loops to identify and promptly address business problems.
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)
Employs the 80-20 rule to avoid perfectionism and minimize time-wasting.
Level 3 Behaviors
(Moderate Experience)
Handles workplace obstacles to maintain focus and manage time efficiently.
Level 4 Behaviors
(Extensive Experience)
Manages teams in streamlining work-related tasks to prioritize highest value tasks firsts.
Level 5 Behaviors
(Mastery)
Keeps current on the latest working models on time management to drive organizational productivity.
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.
