Big Data Engineer Vs. AI Engineer Vs. ML Engineer

Data is called Big Data when it is so large that it cannot be stored, processed, or analyzed using traditional methods. AI ML Course trained engineers who are professionally equipped to test, maintain, evaluate, and develop such data infrastructures to facilitate an organization’s growth is called Big Data Engineers

Some of the responsibilities of Big Data engineers include:

• Collaboration with various stakeholders
• Creating structured data and systems to collect and process data
• Creating data architectures to meet business requirements
• Using ETL process
• Designing and executing software systems
• Data mining

Big Data Engineer can be a promising career for individuals who are strongly skilled in C++, Python and Java, ETL and data warehousing, Apache Spark, Hadoop, Data mining and modeling, Databases and SQL, IBM DataStage, Pentaho, Talend, and Informatica and various operating systems such as Unix, Linux, Windows, and Solaris

Machine Learning

Machine Learning or ML is meant to teach a machine how to arrive at inferences and decisions based on past experiences. It involves the identification of patterns and analysis of past data to reach the solution without involving human experience. This method is time and effort-saving for human beings.

Machine Learning Engineer

The main purpose of ML engineers is to make pre-prepared models ready for production. Achieving this is a result of the execution of multiple activities such as model optimization, model management, containerization, deployment, A/B testing, and monitoring model performance post deployment. The skill sets required to achieve these objectives are data modeling, software engineering, ML frameworks, ML conceptual knowledge, programming, data structures, and statistics

Some of the roles and responsibilities of an ML engineer are as follows:

• Deployment of ML and DL models to production
• Model optimization for better performance, memory, and latency
• Testing inference on various hardware including CPU, GPU, edge devices
• Monitoring model performance, debugging and maintenance
• Version control of experiments, models, and metadata
• Develop custom tools for optimizing the complete deployment workflow

Artificial Intelligence

An idea that first came into the public view in the first half of the 20th century and made it to the news by beating the then world chess champion, Gary Kasparov was Artificial Intelligence. AI has made a breakthrough in most industries and in our day-to-day lives. Using mobile phones to shop and pay digitally, movie recommendations, Google maps, or even asking Alexa to play our favorite songs are examples of AI applications.

Artificial Intelligence or AI is used to help human beings to make better work decisions and help them live more meaningful lives which does not involve too much physical labor on the human being’s part. The phenomenon by which this goal is achieved involves enabling digital computers or robots to perform activities that are associated with the intelligence of human beings. It is commonly called AI. Its purpose is to manage the complexity of interconnected groups, organizations, individuals, or institutions in a way that benefits humanity. Some features that keep AI technology in demand are automation, analysis and accuracy, and enhancement of products and business processes.

Scope In Artificial Intelligence

The majority of Indian companies are seeking to hire candidates with AI skills. The candidates who have been hired have seen a 60-70% increase in their average pay scale. There is a noticeable demand-skill gap, and the demand is expected to increase in the coming years, thereby making AI skills as necessary skills to possess. There are a number of roles an AI expert can work in. Data Scientist, AI Analyst/Specialist, Research Scientist, Product Manager, and Robotics Scientist are some of the most interesting job profiles in this area. You can look at taking up any of these roles if:

• Your foundation in Mathematics and programming languages such as Python or Java is strong and you have an interest in learning new machine learning languages.
• You have a strong understanding of data analytics skills and writing algorithms.

In this article, we will take a deeper look at the job profile of an AI engineer

AI Engineer

Let us find out what are some of the critical information you should be aware of if you want to become an AI engineer:

AI engineers are responsible for bringing autonomy to the models in production. They should have a sound understanding of how AI works because AI engineers are responsible for imparting human intelligence to machines. These engineers are highly focused on research and finding the right model to solve the task in the production stage. Therefore, they combine large amounts of data through intelligent algorithms and iterative processing. Such engineers produce intelligent autonomous models and embed them into applications. Therefore, the deployment of reverse-engineering of human traits into machines becomes extremely important for an AI engineer.

Roles & Responsibilities Of An AI Engineer

AI engineers are expected to be strongly skilled in areas such as cognitive science, deep learning, and NLP and know the production platforms such as Microsoft Azure, Amazon AWS, GCP, and AI services well. An AI engineer is expected to carry on the following activities on a workday:

• Develop scalable, flexible, and reliable APIs to integrate data products and source them into applications.
• Create and execute intelligent AI algorithms into functions
• Test and execute models.
• Develop architecture and maintain the same using leading AI frameworks.
• Use tools for continuous integration and version control for tracking model iterations and other code updates.
• Develop MVP applications for all activities, right from model development to model testing.
• Create user interfaces to display a more detailed view of the models.
• To build infrastructure as a code
• Collaborate with business stakeholders to build AI solutions used to ensure that the business goals and analytics are aligned.

To become an AI engineer, it is necessary to have a graduate degree in  Mathematics, Statistics, Economics, Computer Science, IT, Linguistics, Cognitive Science or any engineering background. As an AI engineer working in India, you can expect to have a salary amounting to more than 1,500,000 INR. With seniority, the package can increase to become INR 50 lakhs per annum