What are the Roles and Responsibilities of an Artificial Intelligence Engineer

What are the Roles and Responsibilities of an Artificial Intelligence Engineer | Artificial Intelligence and Machine Learning | Emeritus

We live in the digital era, and new technologies that enable the automation of processes are rapidly coming up. This digital innovation has created many opportunities in Artificial Intelligence (AI), such as Artificial Intelligence Engineer Roles.

However, before delving into the Artificial Intelligence Engineer roles and responsibilities, we need to easily understand what is AI (Artificial Intelligence)?

AI is a segment where scientific research, theories and advanced technologies are combined to create algorithms that can imitate human intelligence. AI-powered machines can store and analyse data to generate insights such as trends, user behaviours, business insights, etc., to predict events and make future projections. AI can also greatly mimic human faculties of reading, seeing, and speaking.

Today, businesses are increasingly deploying AI systems to learn about their customers, understand market trends, predict future needs and scenarios etc. This kind of AI technology is only expanding its footprint and creating many great opportunities for Artificial Intelligence Engineer roles in almost every industry.

Artificial Intelligence Engineer Job Description

AI engineering is a vast field, and the artificial intelligence engineer’s responsibilities include problem-solving by creating innovative AI products. They are also responsible for maintaining the existing AI systems and infrastructure. The AI Engineer would be a great exponent of data analytics and can help businesses improve operational efficiency, profitability, sales, and customer experience and create new SaaS solutions.

Since AI is now being integrated into almost every industry vertical, the artificial intelligence engineer’s roles and responsibilities have also expanded to include areas such as:

Software designing – AI engineers need to be well-versed in machine learning, model building and validation. They have to evaluate and decide whether an AI system is capable of serving the purpose it was built for or not.

Creation and deployment of AI algorithms – Intelligent AI algorithms work together with iterative processing to allow software automation. The artificial intelligence engineer’s responsibilities include writing code essential for the machine’s functioning.

Building data science infrastructure – AI is predominantly used for data extraction and analytics. That’s why the artificial intelligence engineer’s responsibilities also include setting up and managing the AI infrastructure.

Data analytics – Artificial Intelligence Engineers collect data and analyse it using machine learning algorithms to identify shortcomings. Artificial intelligence engineer responsibilities include ensuring that the AI tools are updated in sync with the breakthroughs and continue to deliver operational advantage to the users.

Natural Language Processing – With the emergence of smart automation and voice controls, prominent artificial intelligence engineer roles include Natural Language Processing. Voice assistants such as Siri or Alexa, self-driving cars, etc., depend on an accurate and swift understanding of human speech, and AI engineers make it possible.

Image Processing – AI is being used in surveillance and monitoring globally. These systems can observe the surroundings and react to each scenario as per parameters set by the artificial intelligence engineers who build them. Thus, image processing is also among the artificial intelligence engineer’s responsibilities now.

How to Become Artificial Intelligence Engineer

With such diversification of artificial intelligence engineer roles, aspirants must master the various technologies necessary to excel in the field. You will have to master the following technologies to become capable of efficiently handling artificial intelligence engineer roles and responsibilities:

Machine Learning – You would need to have machine learning expertise.

Data Modelling – Data modelling is critical to machine learning, and artificial intelligence engineers need to have the ability to identify the best algorithm to solve a given problem and to train those AI models.

Statistics – Statistics are the key to understanding data science and extracting insights to achieve desired results.

Programming– If you are willing to become an artificial intelligence engineer, then programming proficiency will be essential. It would help if you learned common programming languages such as Python. There are several highly impactful and reputed data science courses that you can undertake to achieve your desired programming know-how.

Databases – You must be capable of creating, managing and updating databases and extracting useful insights from the stored data.

Artificial Intelligence Engineer Career Path

Artificial intelligence engineers have plenty of career options now as new artificial intelligence engineer roles are being created in almost every industry. Here are some of the key opportunities that aspirants can avail of:

Data Scientist – A data scientist’s role requires identifying a problem, researching it, finding the right data, structuring, analysing and presenting the data in the form of actionable insights for business growth. The candidates will need to undergo a data science course that helps them learn programming (SAS, R, Python), storytelling and visualisation, statistical and mathematical abilities, Hadoop, SQL, and Machine Learning.

Data Analyst – A data analyst is a crucial connection between data scientists and business analysts. Data analysts are responsible for organising and analysing the available data to answer the organisation’s queries. The ideal candidate would be one with a data science or data analytics certification and good programming and mathematical skills.

Data Engineer – A data engineer is responsible for developing, deploying, managing and optimising the data infrastructure and sources. The right candidate would have undertaken a data science certification and is well versed with skills such as NoSQL, MongoDB, Cassandra DB, Java, Scala, and frameworks such as Apache Hadoop.

Courses for artificial intelligence engineers

You can significantly enhance your suitability for artificial intelligence engineer roles by opting for a data science certification online from reputed platforms such as Emeritus India.

Emeritus India is a reputed learning platform that brings world-class online and in-person learning experiences in IT and AI. The company offers the best learning opportunities facilitated by its collaboration with over 50 top-tier universities across the United States, Europe, Latin America, Southeast Asia, India and China.

You can check out some of the IT Diploma options from Emeritus India that can help you make a career in this coveted field

Artificial Intelligence is the most advanced and rapidly growing engineering stream and a highly rewarding career. But there’s also a lot of competition. Hence, it is always recommended to upskill with certification courses from reputed platforms.

About the Author

Senior Content Contributor, Emeritus Blog
Varun, a seasoned content creator with over 8 years of diverse experience, excels in crafting engaging content for various geographies and categories. Leveraging this expertise, he seamlessly translates complex concepts into enriching educational content for the EdTech domain. His keen understanding of research and life experiences helps him resonate with students and create fact-based content. He finds solace and inspiration in music, nurturing his creativity for content creation.
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