Top 12 Career Opportunities in Artificial Intelligence: A Complete Guide

In recent years, the demand for artificial intelligence (AI) talent has skyrocketed as businesses across industries embrace the technology to stay competitive. According to the Economic Times, AI specialists can earn a salary premium of up to 40-80% compared to traditional IT roles. This surge in demand has made career opportunities in artificial intelligence the most promising and lucrative options available today. Pursuing a career in artificial intelligence offers the potential for significant financial rewards. It also provides a chance to work at the forefront of technological innovation, opening up exciting and diverse career paths for professionals in the field. This blog explores the top career options available in the AI field.

Top Career Opportunities in Artificial Intelligence

AI job hiring in India has increased by 32% in recent years, indicating a significant demand for qualified professionals. This surge is driven by the widespread adoption of AI technologies across various sectors, including healthcare, finance, retail, and more. This section outlines the top career opportunities in artificial intelligence, each offering unique roles and responsibilities in this rapidly growing field.

1. Artificial Intelligence Specialist/Developer

AI specialists/developers design, develop, and implement AI solutions that enhance and automate processes within various industries. They work on creating intelligent systems that can perform tasks traditionally requiring human intelligence, such as speech recognition, decision-making, and visual perception. Their role involves researching and utilizing machine learning algorithms, neural networks, and natural language processing to build AI models. They collaborate with data scientists, software engineers, and other stakeholders to integrate AI technologies into applications.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for artificial intelligence jobs:

• A bachelor’s/master’s degree in computer science, artificial intelligence, or a related field. 
• Certification in AI-related technologies or methodologies is preferred. 
• A minimum of 1 year of professional experience in AI development is required.
• Proficiency in programming languages like Python, C++, R, or Java.
• Experience with popular AI and ML libraries and frameworks (e.g., TensorFlow, PyTorch, Keras, scikit-learn).
• Strong understanding of machine learning algorithms, deep learning architectures, and statistical methods. 
• Experience with supervised and unsupervised learning techniques.
• Knowledge of data preprocessing, feature engineering, and data visualization techniques.
• Familiarity with software development principles and version control.

ii. Average Salary Range: ₹6 LPA – ₹20 LPA

Also Read: AI Engineer Salary in India

2. Machine Learning Engineer

The field of machine learning offers a variety of career opportunities in artificial intelligence. ML engineers work with large datasets to train and fine-tune models that can make predictions or decisions based on input data. Their responsibilities include data preprocessing, feature engineering, model selection, and evaluation. Machine learning engineers also deploy models into production environments and monitor their performance. They collaborate closely with data scientists and software developers to integrate machine learning solutions into products and services, optimizing them for efficiency and scalability.

If you are looking for a course to learn all these relevant skills, enroll in a machine learning course. This course will help you master Python and top machine learning algorithms and earn a certificate accredited by IIT-Madras Pravartak.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for machine learning jobs:

• A bachelor’s or master’s degree in computer science, data science, or a related field.
• Proven experience (1-3 years) in machine learning, data science, or AI roles.
• Proficiency in programming languages, such as Python, R, or Java.
• Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
• Strong understanding of algorithms, data structures, and software design principles.
• Familiarity with cloud platforms (e.g., AWS, Azure) and big data technologies (e.g., Hadoop, Spark).
• Excellent problem-solving skills and analytical thinking abilities.

ii. Average Salary Range: ₹8 LPA – ₹25 LPA

3. Data Scientist

Exploring data science opens up numerous career opportunities in the artificial intelligence field. A data scientist is responsible for extracting insights and knowledge from structured and unstructured data. They utilize statistical methods, data analysis techniques, and machine learning algorithms to analyze and interpret complex data sets. Data scientists identify trends, patterns, and correlations in data to help organizations make data-driven decisions. They often work on predictive modeling, clustering, and classification tasks. 

If you want to become an expert in this field, check out the data science course with a placement. This course will provide you with an opportunity to become job-ready and learn the essential skills. 

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for data science jobs:

• A bachelor’s degree in data science, computer science, statistics, mathematics, or a related field. 
• Good understanding of machine learning algorithms (deep learning algorithms, regression algorithms, etc.). 
• Strong programming skills with proven experience in crafting, prototyping, and delivering advanced algorithmic solutions.
• Experience in extraction from structured/unstructured text (knowledge or statistics-based).
• NLP algorithm implementation experience as well as the ability to modify standard algorithms.
• Experience with neural networks and deep learning frameworks (such as Keras, TensorFlow).
• Familiarity with database queries and data analysis processes (SQL, SAS, Python).
• Strong understanding of data visualization tools and techniques, with experience using software like Tableau, Power BI, or Matplotlib.
• Ability to extract, transform, and load (ETL) data from various sources, ensuring data quality and integrity for analysis.

ii. Average Salary Range: ₹10 LPA – ₹30 LPA

4. AI Research Scientist

If you are passionate about technology and love exploring new ideas, an AI research scientist could be your dream job. This role is all about diving into uncharted territories of artificial intelligence, experimenting with new algorithms, and seeing just how far AI can go.

The job involves a lot of research, testing new ideas, and sharing their discoveries in academic papers. They might focus on areas like deep learning or natural language processing. These scientists often work with universities, research labs, and companies to create groundbreaking AI solutions that can change the world.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for an AI research scientist:

• A bachelor’s or master’s in computer science/electrical engineering/electronics and communications engineering, AI/ML, or a relevant technical field.
• Excellent skills in natural language processing, computer vision, and multimodal AI systems with strong deep learning fundamentals.
• Proficiency in Python and/or other programming languages, experience with PyTorch framework, or other machine learning and scientific libraries.
• Familiarity with uncertainty estimation methods in deep neural networks.
• Demonstrated deep learning and software development experience with open-source contributions and participation in AI/coding challenges.
• Experience with Transformer and Foundation models.
• Research experience in data-efficient and adaptive AI algorithms design and development such as domain adaptation, active learning, etc.

ii. Average Salary Range: ₹12 LPA – ₹35 LPA

5. Robotics Engineer

As a robotics engineer, you will have unique career opportunities in artificial intelligence to design robots that perform a wide range of tasks. A robotics engineer designs and develops robotic systems for various applications, including manufacturing, healthcare, and service industries. They work on creating robots that can perform specific tasks autonomously or with minimal human intervention. 

This job involves designing mechanical components, integrating sensors and actuators, and developing control algorithms. Robotics engineers also work on programming robots to perform tasks such as assembly, inspection, and manipulation. They collaborate with multidisciplinary teams, including mechanical engineers, software developers, and control systems experts, to create efficient and reliable robotic solutions.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to become a robotics engineer:

• A bachelor’s degree in robotics engineering, mechanical engineering, electrical engineering, computer science, or a related field.
• Hands-on experience in the robotics domain, with a proven track record of designing and implementing robotics projects.
• Proficiency in programming languages commonly used in robotics such as C/C++, Python, ROS (Robot Operating System), etc.
• Strong understanding of robotics principles, kinematics, dynamics, control systems, and sensors.
• Experience with CAD software for designing robotic components and systems.

ii. Average Salary Range: ₹6 LPA – ₹18 LPA

6. Computer Vision Engineer

A computer vision engineer specializes in developing algorithms and systems that enable machines to interpret and understand visual information. They work on tasks such as image and video analysis, object detection, facial recognition, and image segmentation. Computer vision engineers use deep learning and machine learning techniques to build models that can process and analyze visual data. They apply their expertise in industries such as autonomous vehicles, surveillance, healthcare, and augmented reality.

Specializing as a computer vision engineer provides exciting career opportunities in artificial intelligence. You’ll be developing systems that allow machines to see and interpret visual information, a key aspect of many advanced AI applications.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for computer vision engineer jobs:

• A bachelor’s degree in computer science, electrical engineering, or a related technical field. 
• Relevant work experience (machine learning/artificial intelligence/computer vision/deep learning).
• Experience in designing and implementing distributed software systems (e.g. Java, C++, or Python).
• Research or industry experience in artificial intelligence, computer vision, machine learning (ML) models, ML infrastructure, natural language processing, or deep learning.
• Knowledge of image and video processing techniques, including filtering, edge detection, and motion analysis.
• Strong understanding of model evaluation metrics specific to computer vision tasks, such as Intersection over Union (IoU), mean Average Precision (mAP), and pixel accuracy.
• Experience in working with software development in embedded real-time systems.
• Knowledge of camera calibration, 3D reconstruction, and multi-view geometry for applications in augmented reality, robotics, or autonomous vehicles.

ii. Average Salary Range: ₹7 LPA – ₹22 LPA

7. Big Data Engineer

Big data engineers are pivotal in unlocking career opportunities in artificial intelligence by managing the massive datasets that fuel AI systems. These professionals design, build, and manage the infrastructure and tools required to process and analyze large volumes of data. They work with big data technologies such as Hadoop, Spark, and Kafka to handle data storage, processing, and analysis at scale. 

Furthermore, they are responsible for creating data pipelines that ingest, process, and transform data from various sources. They ensure the data infrastructure is efficient, reliable, and scalable to support data analytics and machine learning initiatives. 

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for big data engineer jobs:

• A bachelor’s degree in computer science, information technology, or a related field. 
• Expertise in Spark framework with Scala language and Pyspark.
• Expertise in ETL data warehousing and cloud concepts.
• Basic understanding of hive, spark, and impala architecture, along with cloud integration concepts.
• Ability to design and create data flow diagrams and do data modeling.
• Expertise in data profiling and decision-making.
• Ability to understand the architecture and design of end-to-end data flow.
• Excellent logical and analytical, troubleshooting, and problem-solving skills.
• Excellent working knowledge of version control systems like GitHub and branching strategies.
• Good knowledge of RDBMS.
• Proficiency in big data technologies such as Hadoop, Spark, or Kafka for processing and analyzing large volumes of data.

ii. Average Salary Range: ₹8 LPA – ₹25 LPA

8. NLP Engineer

The role of an NLP engineer offers numerous career opportunities in artificial intelligence, focusing on teaching machines to understand and generate human language. An NLP (Natural Language Processing) engineer focuses on developing algorithms and models that enable computers to understand, interpret, and generate human language. They work on tasks such as text analysis, sentiment analysis, machine translation, and speech recognition. 

NLP engineers use techniques such as tokenization, parsing, and semantic analysis to process and analyze textual data. They apply machine learning and deep learning models to solve language-related problems. NLP engineers work in various applications, including chatbots, virtual assistants, and language-based recommendation systems, collaborating with linguists and software developers.

Note: You can learn about different applications of NLP like information retrieval, text classification, and language modeling to master the most exciting branch of artificial intelligence by enrolling in a natural language processing course.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for NLP engineer jobs:

• Bachelor’s degree in computer science, mathematics, computational linguistics, or a related field. 
• Understanding of NLP techniques for semantic extraction techniques, text representation, data structures, and modeling.
• Ability to effectively design software architecture.
• Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis, etc), statistics, and classification algorithms.
• Knowledge of Python and Java.
• Ability to write robust and testable code.
• Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn).
• An analytical mind with problem-solving abilities.

ii. Average Salary Range: ₹6 LPA – ₹20 LPA

9. AI Product Manager

With numerous AI job opportunities emerging, an AI product manager plays a crucial role in overseeing the development and implementation of AI-driven products and solutions. They work closely with cross-functional teams, including data scientists, engineers, designers, and business stakeholders, to define product requirements and strategies. 

Furthermore, these professionals identify market opportunities and customer needs, guiding the product vision and roadmap. They prioritize features, manage the product lifecycle, and ensure that AI products meet business objectives and deliver value to customers. AI product managers also stay informed about industry trends and advancements in AI technology to keep products competitive.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for AI product manager jobs:

• A bachelor’s in computer science or a related field. 
• Strong understanding of AI and machine learning concepts, including common use cases, limitations, and ethical considerations.
• Experience in product management, with a track record of successfully launching AI-driven products or services.
• Proficiency in data analysis tools and techniques.
• Knowledge of Agile methodologies and experience with project management tools like Jira, Asana, or Trello.
• Experience with GenAI/ML products, product analytics tools, user behavior analytics, and reporting tools is a definite plus. 

ii. Average Salary Range: ₹10 LPA – ₹30 LPA

10. AI Data Analyst

An AI data analyst focuses on analyzing and interpreting data to support AI and machine learning initiatives, opening up numerous career opportunities in artificial intelligence. They work with large datasets to identify patterns, trends, and insights that can inform decision-making. AI data analysts perform data cleaning, preprocessing, and visualization tasks to prepare data for analysis. 

They collaborate with data scientists and machine learning engineers to develop and evaluate models, ensuring the data is accurate and relevant. AI data analysts also create reports and dashboards to communicate findings to stakeholders, helping drive data-driven decisions within the organization. 

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for AI data analyst jobs:

• A bachelor’s degree in computer science or a related field. 
• Proficiency in data analysis tools and software such as SQL, R, Python, Excel, etc.
• Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy.
• Strong familiarity with existing GenAI/LLM/ML standards.
• Familiarity with machine learning and predictive modeling techniques.

ii. Average Salary Range: ₹5 LPA – ₹15 LPA

11. Business Intelligence Developer

A business intelligence developer designs and implements BI solutions to help organizations make data-driven decisions. They work on creating dashboards, reports, and data visualizations that provide insights into business performance and trends. BI developers gather and analyze data from various sources, ensuring data quality and accuracy. 

They use BI tools such as Tableau, Power BI, and QlikView to build interactive and user-friendly visualizations. BI developers collaborate with business analysts, data analysts, and other stakeholders to understand reporting requirements and provide actionable insights to support strategic decision-making.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for business intelligence developer jobs:

• A bachelor’s degree in computer science, information technology, or a related field. 
• Strong understanding of testing principles, manual testing methodologies, and software development life cycle.
• Solid knowledge of data manipulation techniques, data validation, and data integrity concepts.
• Proficiency in designing and executing test scenarios, cases, and scripts.
• Familiarity with bug tracking and test management tools (e.g., JIRA, TestRail, Zephyr).
• Experience working in an Agile/Scrum development environment.
• Strong proficiency in SQL and database technologies (e.g., SQL Server, PostgreSQL, MySQL).
• Hands-on experience with ETL tools and processes (e.g., SSIS, Informatica, Talend).
• Hands-on experience in DAX.
• Proficiency in business intelligence and data visualization tool Power BI.
• Solid understanding of data warehousing concepts and methodologies.
• Experience with programming languages such as Python, R, or Java is a plus.

ii. Average Salary Range: ₹6 LPA – ₹18 LPA

12. AI Ethics and Policy Specialist

An AI ethics and policy specialist is like a watchdog for the ethical side of AI technology. They make sure that AI systems are created and used in a way that’s fair and responsible. Think of them as the ones keeping an eye on how these smart systems affect our society, especially when it comes to things like privacy, fairness, and making sure there’s no bias.

They work closely with researchers, policymakers, and leaders in the tech industry to set up rules and standards. They’re also the ones who help educate the public about why it’s important to think about these ethical issues. Basically, they advocate for using AI in ways that are good for everyone and keep us safe from any negative impacts. It’s a role that mixes a bit of tech know-how with a big dose of social awareness, making sure that as AI grows, it does so in a way that benefits all of us.

i. Required Qualifications and Skills:

Here is a list of the skills and qualifications required to apply for an AI ethics and policy specialist:

• A bachelor’s or master’s degree in law, public policy, ethics, computer science, or a related field.
• Strong understanding of ethical considerations and potential risks associated with AI.
• Familiarity with relevant AI regulations and compliance requirements.
• Excellent communication and interpersonal skills, with the ability to build relationships and influence diverse stakeholders.
• Analytical and problem-solving skills, with the ability to identify and mitigate risks.
• Project management skills and the ability to work independently and as part of a team.
• Familiarity with data science and/or machine learning concepts is a plus.

ii. Average Salary Range: ₹8 LPA – ₹20 LPA

Top Companies Hiring for Artificial Intelligence Roles

The artificial intelligence industry is booming with numerous top companies actively hiring for various AI roles. These companies are leading the charge in AI research, development, and application, and offer exciting career opportunities in artificial intelligence. Following are some of the top companies hiring for artificial intelligence roles:

• Google: The company is leading the AI revolution with projects like Google AI and DeepMind. It offers roles in AI research, machine learning engineering, and data science.
• Microsoft: Microsoft focuses on AI research and development, including cloud-based AI solutions. It offers opportunities in Azure AI, Cortana, and AI-based productivity tools.
• Amazon: Amazon utilizes AI in Amazon Web Services (AWS), Alexa, and retail analytics. It provides roles in machine learning, data science, and AI software development.
• IBM: IBM is known for its AI platform Watson and extensive AI research. It offers roles in AI consulting, research, and application development.
• Meta: Meta focuses on AI for social media algorithms, augmented reality, and more. It has positions available in machine learning, AI research, and computer vision.
• NVIDIA: NVIDIA specializes in AI hardware and software, particularly in graphics and gaming. It offers roles in AI software development, hardware engineering, and research.
• Apple: Apple incorporates AI in products like Siri, Apple Maps, and more. It provides opportunities in AI research, machine learning, and product development.
• Accenture: Accenture provides AI consulting services and custom AI solutions. It has positions in AI strategy, consulting, and implementation.
• Tata Consultancy Services (TCS): Tata Consultancy Services (TCS) offers AI solutions across various industries. It provides roles in AI development, data science, and consulting.

Conclusion

With the surge of career opportunities in the artificial intelligence (AI) field, it is imperative to understand the fundamental principles of AI and the various employment avenues it offers. A thorough understanding will equip you to secure top positions in AI. Hiring candidates with AI skills has become essential for employers to meet their technological demands. Aspiring AI professionals must acquire the requisite technical competencies to thrive in this dynamic and evolving industry.

Looking for a beginner-friendly guide to learning and mastering AI? Start your journey with the AI roadmap and prepare yourself for a future full of possibilities.

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