Full Stack Developer is a developer who works on both – frontend and backend parts of the application. They are skilled to deal with all kinds of work such as databases, servers, system engineering, architecting, and client communication that are required to make complete products. Full Stack Developers have functional knowledge of all the layers of software development. They simply take an idea and turn it into a finished product independently. They know multiple languages, especially web languages, software development approaches, modern concepts, and various tools that are needed to build a full-fledged web/mobile app.

Data Scientists encompass collecting, analyzing, and interpreting large volumes of data to derive insights and build predictive models, often using techniques like machine learning and extract relevant information from it. They apply their mathematical, statistical, programming skills to analyze, data visualization, ultimately leading to data-driven decision-making and interpret the data available to companies. Companies use these insights to create business strategies.

Data Architect designs, builds, and manages an organization's data infrastructure, design platforms for processing massive data into strategic information for business, ensuring data is accessible, secure, and supports business needs, working closely with data engineers and stakeholders to create and maintain data-centric solutions. They design, create, supervise, administer, implement, and manage data structures.

Data Engineer designs, builds, and maintains data pipelines and infrastructure to ensure data flows efficiently and securely, preparing it for analysis and decision-making. They also focus on data quality, security, and scalability, collaborating with data scientists and analysts. Data Engineers extract & process the information that is later used by data scientists and analysts. They manage database infrastructures, develop maintenance algorithms, and automate fetch & cleanup processes. They make the analysis and interpretation of information more effective, safe, & useful.

AI Specialists leverage technologies to solve complex business problems via technological innovation. They are responsible for designing, developing, and implementing AI models and algorithms that can automate processes, enhance decision-making, and provide valuable insights from data for businesses. AI Specialists create and train machine learning models, analyse large datasets, and develop solutions tailored to specific business needs. They collaborate closely with data scientists, software developers, and business stakeholders to ensure the successful deployment and integration of AI technologies. AI Specialists are essential for companies due to their ability to drive efficiency, innovation, and competitive advantage. Their AI and machine learning (ML) expertise enables organisations to automate repetitive tasks, gain deeper insights from data analysis, and develop new products and services that meet market demands.

ML Engineer is a professional in the field of information technology who specializes in the development of self-contained artificial intelligence (AI) systems that automate the usage of prediction models. The AI algorithms capable of learning and making predictions are designed and built by ML Engineers.ML engineer generally collaborates with other members of a broader data science team, including data scientists, administrators, data analysts, engineers, and architects. Depending on the scale of the firm, they might additionally interact with groups outside of their teams, including the IT, software development, sales, or web development teams. ML engineers connect data scientists who focus on statistical and model-building work as well as the development of machine learning and AI systems. Large amounts of data need to be evaluated, analyzed, and organized. Tests need to be run, and machine learning models and algorithms need to be optimized.