There are currently 45,000 jobs related to artificial intelligence (AI), with data scientists and machine learning (ML) engineers being the most in-demand careers in India.
A report by technical staffing firm TeamLease Digital presents these findings analyzing the potential of AI across multiple industries. According to the report, growing interest in scalable ML applications is driving a surge in demand for AI professionals who are proficient in scripting languages and can build traditional ML models.
Below are some of the findings of the report.
• Data and ML Engineers can earn up to INR 1.4 lakh per year and Data Architects can earn up to INR 12 lakh.
• Those with 8 years’ experience in similar field can get higher salary of Rs.25 lakh to Rs.45 lakh per annum.
• Upskilling yourself with AI skills is becoming increasingly important when it comes to career growth and employability. There are long-term benefits for individuals and their careers who invest in AI skills.
• To build an AI-enabled workforce, 37% of organizations prefer providing employees with relevant tools, and 30% of organizations require AI learning initiatives to unlock hidden talent in their workforce. It is said that
• A whopping 56% of organizations also indicate that the necessary initiatives are in place to close the talent gap between AI demand and supply.
What exactly do these people do?
Data Engineer: These engineers collect and transform data from multiple resources and build and manage the systems that generate this data.
Clean and transform ingested data for scrutiny by data scientists and analysts. To build architectures and data systems, use the same guidelines used in software development to write complex queries and make data actionable.
I also have knowledge of algorithms and some of the important programming concepts.
Machine Learning Engineer: ML engineers are engineers dedicated to researching, building, and designing self-executing artificial intelligence (AI) systems for automating predictive models.
They design and create AI algorithms capable of learning and predicting that define machine learning (ML).
Data Architect: Responsible for defining the policies, procedures, models, and technologies used to collect, organize, store, and retrieve organizational information.
Experts in developing an organization’s data strategy, including data quality standards, data flow within the organization, and data security. It is this data management specialist’s vision that translates business requirements into technical requirements.
