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 IV 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 step-by-step procedures for developing new and enhanced software products.
Level 2 Behaviors
(Light Experience)
Uses specific programming languages and platforms to write code and create software programs.
Level 3 Behaviors
(Moderate Experience)
Works collaboratively with development teams to correct complex errors in software codes.
Level 4 Behaviors
(Extensive Experience)
Trains teams on developing highly responsive user interfaces (UI) to enhance customer experience.
Level 5 Behaviors
(Mastery)
Keeps abreast of the latest industry coding best practices to maximize application readability and performance.
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.
Level 2 Behaviors
(Light Experience)
Supports the development of sophisticated models using structured and unstructured data sets for analysis.
Level 3 Behaviors
(Moderate Experience)
Uses advanced programming languages and software packages to design algorithms and deploy AI models.
Level 4 Behaviors
(Extensive Experience)
Trains new how to recognize immediate issues regarding artificial intelligence.
Level 5 Behaviors
(Mastery)
Leads the program planning, development, and execution of cutting-edge AI software products and models.
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-Analyzing, developing, and applying big data and algorithms to imitate how humans think and learn.
Level 1 Behaviors
(General Familiarity)
Describes the concepts and fundamental statistics of deep learning.
Level 2 Behaviors
(Light Experience)
Conducts research to identify cutting-edge techniques and tools in deep learning.
Level 3 Behaviors
(Moderate Experience)
Deploys accurate deep learning models to support computer vision tasks.
Level 4 Behaviors
(Extensive Experience)
Creates and leverages deep learning models to improve the effectiveness of our business operations.
Level 5 Behaviors
(Mastery)
Champions the adoption of advanced tools in developing language models to solve complex deep learning problems.
Skill definition-The ability and process of implementing new ideas and initiatives to improve organizational performance.
Level 1 Behaviors
(General Familiarity)
Describes the market conditions that impact the business.
Level 2 Behaviors
(Light Experience)
Collects and compiles competitor information for competitive analysis.
Level 3 Behaviors
(Moderate Experience)
Applies technical expertise, business sense, and product knowledge to manage the product lifecycle effectively.
Level 4 Behaviors
(Extensive Experience)
Coordinates technical and business teams to solve complex and diverse customer problems.
Level 5 Behaviors
(Mastery)
Builds strong business partnerships internally and externally to drive "win-win" business successes.
Skill definition-Executing and completing a task with a high level of accuracy.
Level 1 Behaviors
(General Familiarity)
Explains why attention to detail plays an important role in own function or unit.
Level 2 Behaviors
(Light Experience)
Performs assigned responsibilities according to standard procedures and standards.
Level 3 Behaviors
(Moderate Experience)
Implements a variety of cross-checking approaches and mechanisms.
Level 4 Behaviors
(Extensive Experience)
Demonstrates expertise in quality assurance tools, techniques, and standards.
Level 5 Behaviors
(Mastery)
Designs techniques for measuring the cost and impact of errors.
There are 8 hard skills for AI Engineer IV, Software Engineering, Artificial Intelligence (AI), Cognitive Computing, etc.
5 general skills for AI Engineer IV, Cloud Computing, Deep Learning, Machine Learning, etc.
9 soft skills for AI Engineer IV, 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 an AI Engineer IV, he or she needs to be skilled in Innovation, be skilled in Attention to Detail, and be skilled in Time Management.
