Artificial Intelligence Job Description: Skills | Roles

Who Is an Artificial Intelligence Engineer?

Artificial Intelligence offers machines the capability to exhibit human-mimicking intelligence. AI and Machine Learning tasks are performed by some designated individuals called Artificial Intelligence Engineers. 

They hold knowledge, skills, and hands-on experience in domains like software engineering, data science, data handling, programming, etc. The AI engineer role requires the usage of advanced systems, tools, and processes to build AI applications that do the following: 

• Sentimental analysis 
• Visual identification or perception 
• Language Translation and much more. 

They generate, implement, verify, and maintain an organization's AI applications and systems. Artificial intelligence engineers run popular platforms like Netflix, YouTube, Spotify, etc. 

Artificial Intelligence Engineer Job Responsibilities 

What do artificial intelligence roles and responsibilities look like? Let's explore: 

Develop and Maintain AI strategies 

AI engineer responsibilities include understanding business objectives and utilizing AI models to make business decisions and develop strategies. They also need to ensure timely optimization and proper maintenance of AI processes. 

Building Data Science Infrastructure

You will find this depicted in the job description AI as developing and maintaining databases, data warehouses, and data lakes. It will also encompass performing activities like data preprocessing, cleansing, and similar tasks. 

Productionization of AI Networks

Artificial intelligence roles and responsibilities include transitioning ML models from development environments to production systems. The productionization of AI networks offers results like detecting time series anomalies, event correlation, and user experience prediction. 

Design and Implement ML Algorithms

Being a part of an AI engineer role, designing and implementing requires handling massive datasets to train the algorithms. It is further used to learn and train the AI for cognitive tasks and subsequently to deploy them to serve the customer base. 

Developing Infrastructure for Data Transformation

The stated job responsibility is carried out by handling the data, storing and managing it, and developing data processing and Machine Learning frameworks. It involves handling issues like outliers, missing values, and inconsistencies. 

Automate Processes by Utilizing Machine Learning

The AI engineers automate the processes by hyperparameter optimization, model and feature selection, and data preprocessing via the utilization of transfer learning and pre-trained models. They also use automation tools to identify patterns, analyze large data sets, optimize processes, and predict future trends. 

Collecting and Interpreting Relevant Data

Among the AI engineer responsibilities, professionals will need data analysis. It also involves data handling and processing. For interpretation, the Artificial intelligence job description will include visualization skills for data and the knowledge to apply the AI model. 

Deploy Software in Production

The deployment requires model or software integration into the business process. The AI engineers will verify functionality in each aspect along with the ability to produce effective results through real-time data. The deployment process involves using tools like Docker, Kubernetes, AWS Lamba, and others. 

Use AI to Empower the Organization 

AI engineers contribute the power of AI in organizational growth by utilizing AI for:

• Analytics
• Predictive modeling
• Effective visualization
• Pattern recognition
• Risk management 
• Business process optimization
• Deriving useful and minute insights and much more 

Answer Business Challenges Using AI Software

Businesses face numerous innovative challenges requiring out-of-the-box solutions. AI engineers utilize AI to contribute highly efficient solutions in less time. Further, they can also derive novel insights from AI via techniques learned through prompt engineering. 

Data Modelling

The job description for AI will also include the requirement of the ability to model data. To perform the task, AI engineers will develop and verify the unique machine learning models. They will be deployed via API calls or through embedded code to perform the action. 

Managing and Executing Projects

One important task for AI engineers is managing and executing multiple projects simultaneously. They may also participate in interdisciplinary projects, designing, developing, and maintaining AI-based systems while handling complex network algorithms. AI engineers are also tasked with timely and quality project delivery. 

Programming

Programming is an essential part of the AI engineer role. It is required to -

• Develop algorithms and models 
• Implement models 
• Customization and optimization 
• Handle data
• Debugging 
• Statistical analysis 
• Version control 
• Graphics representation 
• Scalability 

Software Designing

The software design utilizes advanced Machine Learning approaches like deep learning, reinforcement learning, and unsupervised learning. AI engineers carry out detailed design of system architecture and apply design patterns to address challenges. 

Visualizing Data for Deeper Insights

Data visualization requires effective selection and utilization of separate tools for static and interactive visualization. Further, visualization techniques must be chosen, such as geospatial or network visualization, statistical charts, time series plots, or others. AI engineers are responsible for creative visualization. 

Job Roles in Artificial Intelligence

The sector encompasses a variety of AI engineer roles. Here is a basic overview of what they look like. 

Robotics Engineer

They are concerned with developing applications or autonomous machines, also referred to as robots. They are designed to perform human and non-human actions. Both application and research-based roles are available for robotics engineers. The applications expand to industries like automotive, manufacturing, mining, hospitality, and others. 

AI Researcher

AI researchers or AI research scientists carry out research-based work in the field. They are responsible for finding technical solutions to problems, developing innovative solutions, and improving current issues. They are specialists in Machine Learning or Computer vision and experts in statistics, math, and programming. 

NLP Engineer 

NLP engineers are tasked with making machines understand human language. They are concerned with data processing, algorithm selection and implementation, model training and evaluation, integration and deployment, testing and maintenance, and programming machines to analyze natural language data.

Product Manager

With multiple projects running simultaneously in the field of AI, professionals can also choose this management position. They are tasked with delivering the project on deadline with quality. They are also responsible for required improvisation, adhering to the business objectives, and delivering projects that meet market demands. 

Business Intelligence Engineer

These engineers deal with technical data search and collection, data governance, maintaining data quality, and data security standards. They also collaborate with business intelligence analysts to ensure effective outcomes and solve business problems. The business intelligence engineer also contributes to the identification of new features and business opportunities. 

Computer Vision Engineer 

CVEs have to deal with digital signals, video feeds, and analog images when handling visual data. They collaborate with data scientists and build new systems to improve the visual technology value. The computer vision engineer improves the use cases associated with visual recognition systems. 

Deep Learning Engineer 

Deep learning engineers apply their knowledge and skills to data engineering, modeling, and deployment subtasks. These tasks involve defining data requirements, collecting, labeling, inspecting, augmentation, and moving data. Further actions involve searching hyperparameters, defining evaluation metrics, converting code from prototype to production, saving bandwidth, and others. 

AI Designer

The AI designers are known to implement AI solutions in vast industries such as finance, healthcare, retail, etc. The responsibilities encompass handling AI projects completely, from concept to real-life usage. They understand the requirements of the clients and oversee the development of solutions and their performance. Besides designing AI prototypes, they also develop new technologies, AI development tools, and products. 

AI Ethics Specialist

With the potential to utilize AI in any manner and cause harm, professionals are required to control the situation. AI ethics specialists deal with the issue by ensuring the usage of AI in limitations of ethical standards and societal values. They create and enforce ethical frameworks. The AI ethics specialist trains the employees across departments and shapes policies, among other tasks. 

Skills Required for an AI Engineer

The candidates seeking a position as an AI engineer are required to possess field-relevant and soft skills. The specific requirements here are: 

Programming 

The AI engineer responsibilities require knowledge and hands-on experience with C++, Java, Python, R, or any other specified language. The knowledge will be critical to designing programs, model deployment, analysis, and decision-making. 

Mathematics 

Algebra, statistics, calculus, probability, and similar concepts are part of an AI engineer's daily routine. These are required for using algorithms and carrying out a variety of functions with Machine Learning models. 

Analysis and Visualization 

These skills are significant for the roles concerning analysis, decision-making businesses, and associated requirements. Companies utilize data for analytics, and professionals must deduce necessary patterns and trends and derive insights. It is possible only in the presence of effective analytical and visualization skills. 

Business Intelligence 

If you are aiming for administrative or leadership roles, knowledge of running the business and the ability to solve associated problems is preferred among the desired candidates. The individuals possessing a combination of technical and business knowledge, such as market basics, competition, and business operation, are the ones being discussed here. 

Collaboration 

AI caters to all industries and fields. Hence, multidisciplinary collaboration among individuals happens here. Building skills to work in coherence with different departments and teams is among the necessary skills expected in the candidate. 

Critical Thinking 

The world of AI harbors novel challenges in routine tasks. A problem-solving mind with a critical thinking approach is essential to keeping professionals on board. Developing critical thinking helps in the long run and helps you reach a logical conclusion by treading along an informed path. 

Sample AI Job Description

Excelling with state-of-the-art technology to provide innovative and effective solutions in the field of AI, our [company] is seeking skilled and passionate AI engineers. Harboring multidisciplinary projects and catering primarily to IT industries, we seek professionals who are dedicated to career growth. Concerning AI, they must have hands-on experience in deep learning, real-life use cases of AI, and demonstrated quantitative results. We will offer you the platform for both professional and personal development and a culturally diverse team. Begin your journey to bring a change and feel confident with your abilities with us. 

Objectives of the AI Engineer Role 

• Adhere to the company's objectives and values. 
• Focus on the requirements and take effective risk assessment and mitigation strategies via AI. 
• Offer a solution or an optimistic approach to AI-based problems 
• Work alongside the cross-functional teams for business growth 
• Maintain ethical standards while delivering a solution

Artificial Intelligence Roles and Responsibilities 

• Utilize Machine Learning concepts to design and develop the model. Validate them for optimization and usability
• Make use of programming languages to develop software and/or applications based solutions 
• Incorporate AI to extract and analyze the data and manage AI infrastructure 
• Contribute to designing, prototyping, testing, training, and supporting procedures among the different teams and projects 
• Document the processes, work on the solutions architecture, and pace up the flow 
• Connect with stakeholders and project teams
• Contribute to different technical projects as per the requirements. This will include but is not limited to, image and natural language processing and data analytics. 

Work Hours and Benefits of AI Engineers 

The current market demands for talented and skilled AI engineers are immense. The passionate candidates in the field get flexible work hours and numerous benefits from the companies. Here is what to expect: 

• Flexible work hours in remote or hybrid settings 
• Various types of industries, including but not limited to disability, accidental death, supplemental life insurance, dental, health, vision, and occupational accidental insurance 
• 401K plan 
• Bereavement leave 
• Paid holidays 
• Sick days 
• Vacation and paid time off 

Courses for Artificial Intelligence Engineers

Artificial intelligence courses are currently in demand. However, the right pick will be the one where you get hands-on experience, a globally recognized certificate, expert guidance, and other perks essential for your development. Simplilearn provides all this and much more with its courses for artificial intelligence engineers. Discover what you can explore here: 

Course	Duration
Professional Certificate Program In Generative AI And Machine Learning	11 months
Post Graduate Program In AI And Machine Learning	11 months
Caltech Post Graduate Program In AI And Machine Learning	11 months
AI For Decision Making: Business Strategies And Applications	3 months
Generative AI For Business Transformation	4 months
Applied Generative AI Specialization	4 months

How to Become an Artificial Intelligence Engineer?

The journey to becoming an Artificial Intelligence engineer can begin whenever you wish to contribute to the field. The pathway to take will depend on your current skill set and position. Look out for what to opt for. If you are an experienced individual, follow along from where you stand: 

School/Graduation: Begin your journey from school by opting for computer science, physics, chemistry, and maths. During graduation, choose computer science or an associated field. Both three-year B. Sc. and four-year B. Tech are accepted. Qualifying for competitive examinations and gaining education from top universities is preferred. 

Post Graduation: While this is not necessary, it gives you an upper hand. Offering in-depth information, better skills, and hands-on practice, if the same is available through other means like jobs and internships, the latter options will work, too. 

Certifications: College-level education is neither entirely updated nor offers industry-specific skills and knowledge. However, certifications do. Requiring a thorough understanding of the concepts and skills, certifications speak for your passion and ability to get the task done in the field. Online certifications are preferred and are now available to take during graduation and post-graduation. Simplilearn even offers credits, thus helping you lower the burden of coursework. 

Experience: After learning and building yourself, the next step is to gain real-world exposure. This comes from working in internships and entry-level jobs. You can also gain experience under professors, research scholars, and post-docs. 

Career Paths Related to Artificial Intelligence 

While we have been discussing the role of an artificial intelligence engineer in the article, most of the information mentioned above also pertains to related career paths. Also, there is more for you to explore. The related career paths are: 

Data Scientist

They recognize technical problems and solve them using data. Data science encompasses handling data through multiple procedures for business growth. They must use tools, algorithms, and processes to carry out their actions. Data scientists differ from data engineers, as the latter are concerned with data management, organization, and building data pipelines, while data scientists analyze and interpret data. 

Data Engineer

Data engineers are mainly concerned with data collection, management, storage, raw data conversion, processing, and other critical tasks that make data usable. The data engineers build data pipelines and work on analytics. Their actions also include optimizing data infrastructure, management, and access. 

UX Developer

UX developers utilize AI to enhance, optimize, and create innovative web page designs, e-commerce platforms, websites, and mobile apps. They also deal with programming languages when designing programs. The AI engineer role creates prototypes for new ideas and contributes to product development. 

Software Engineer

Software engineers are concerned with the development of varying types of software applications. It includes creating web applications, robots, mobile apps, operating systems, and network control systems. They are also responsible for fixing errors, maintaining them properly, optimizing them in a timely manner, and improving the developed systems.

Data Analyst

The data analyst's role majorly emphasizes data collection, cleaning, and interpretation. The insights obtained from data are used in decision-making. The data analysts are required to prepare attractive visualizations of the data. Issues are resolved through diagnostic, descriptive, and perspective analysis. 

Software Architect

Playing a critical role in AI, software architects are majorly responsible for choosing appropriate technologies and processes for software development. Additionally, they are concerned with coding issues and interdisciplinary collaboration. The software architects hold responsibility for challenges occurring during the pre-development stage.

Conclusion 

The Artificial Intelligence Engineer job role is currently in demand. It is a broad field that encompasses a variety of specializations, opportunities to serve in different industries, and roles and responsibilities. While we have enlisted comprehensive information on the Artificial Intelligence-based job, the requirements for specific roles and industries are lower than these. Follow our role-specific articles for separate information on your field of interest. If you are willing to make a career in AI, the Artificial Intelligence Engineer program by Simplilearn is all you need.

FAQs

1. What is the eligibility for an Artificial Intelligence Engineer?

The eligibility criteria for working as an artificial intelligence engineer is at least a bachelor's degree in fields like data science, computer science, or other similar fields. Further, certifications and master's degrees are not necessary but positively influence career trajectory.  

2. What can I do as an AI Engineer?

As an AI engineer, you can choose from a wide range of tasks or specializations. You can specialize in AI security, build data science infrastructure, conduct research, build AI models, perform data transformation, and much more. 

3. What industries are hiring AI specialists?

Almost all industries require and, hence, hire AI specialists. For instance, you can choose among healthcare, retail, e-commerce, automotive, manufacturing, education, etc. 

4. What are the career progression opportunities in the AI field?

You can combine your AI expertise and progress in different fields like management, business, analysis, etc. 

5. What role does data play in AI jobs?

Data can be considered the building blocks of AI jobs. They are used to train models, gain insights, derive information, make decisions, predict, and perform many other actions.