Top AI and ML Job Trends: Startups Vs MNCs

Organizations are collecting massive data generated by a 24/7 connected ecosystem. They leverage this data for insights and a competitive edge. Companies increasingly rely on Artificial Intelligence (AI) and Machine Learning (ML) experts to work on such projects. And the demand for AI and allied expertise with the right skill sets is growing across industries and applications. 

Among the most in-demand jobs within AI are Data Scientist, Machine Learning Engineer, Big Data Engineer, BI Developer, Research Scientist, AI Engineer, and Robotics Scientist. These professionals occupy the top spot and receive high remunerations for their skills and work experience.

The Bureau of Labor Statistics predicts a 15% increase in IT and research jobs from 2019 to 2029, with positions like AI experts and ML engineers earning more than managers. The average annual salary is $140,000 or $71.79 per hour. Entry-level jobs can earn more than $115,000 per year, and the more experienced professionals stand a chance to make up to $200,040 per year.

If you are an IT professional who wants to dream big and carve a career in the hottest technologies, consider registering for the AI and Machine Learning Bootcamp in Chicago. The AI job market is on fire, and the time is perfect for upskilling.

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Why the AI and ML job market is on fire

We are witnessing a high demand for AI and Machine Learning skills. The job market is exploding, and from startups to MNCs, businesses are keen to hire AI professionals. While the Bay Area leads with more than 2,000 AI-centred startups, hiring is global, with more and more MNCs joining the AI-ML hiring bandwagon.

AI and ML are not new, but the focus of late is to build great AI models that can compete with human intelligence and machines. The need is for powerful algorithms that apply to business challenges or research problems. 

Advances in deep learning have also revolutionized computer vision and NLP. As businesses mix and match various technologies to meet customer expectations of improvements in goods, services, and societal benefits, the pace of research is staggering. 

Today every industry is impacted by AI in some ways for providing swift improvements to products and services. AI and ML jobs are thus evolving at a fast pace with a high demand for problem-solving skills using self-learning algorithms integrated into every process, from data analytics to mobile apps. Technologists and hirers are thus requesting cutting-edge AI and ML skills. 

From simple solutions to complex services, AI and ML are getting more and more embedded into our society, and soon, we may not be able to do tasks without digital or “smart” assistance from an AI model. This capability of AI attracts high investments from venture capitalists, governments, and MNCs like Microsoft and Google. In the race for AI implementation, startups focusing on specific business solutions are the rage.

With these technologies emerging as core competencies, we can expect them to be the force behind how we accomplish most tasks in the future. And the demand for AI-ML skills will only rise.

With AI adoption growing among startups and enterprises, businesses boost research and innovation in various operations to lessen industrial and personal pain points.

The following top trends are powering the AI and ML job market:

A. Adoption across most industries and myriad applications

Entire industries are being transformed by AI, from healthcare, banking and finance to e-commerce, industrial operations, and beyond. Academic research is growing, and startups and MNCs alike are ramping up their hiring for tapping the potential in corporate and personal use. So whether it is a startup specializing in AI solutions or an MNC like DeepMind, AI adoption is industry-wide.

B. Variability in companies hiring AI-ML job positions

Another trend is the variability in companies. Although many companies with AI offerings belong to the MNC category, there is a small segment offering niche and customized solutions. These startups are cropping up globally, not confined to Silicon Valley or other tech hubs. While some startups build proprietary AI models, others specialize in offering tailor-made solutions to solve specific business problems.

C. Funding is driving investments in AI

The tech giants are undoubtedly leading the market. Their AI and ML products are offered through cloud platforms, thus enabling the incorporation of AI in various business applications and systems. It is helping smaller firms implement AI as they do not incur expensive in-house research and development. Huge funds and public ventures are some reasons why MNCs can invest massively in developing AI-focused products. The salary packages in MNCs are astronomically high, in line with their corporate policies.

Startups, however, spend much of their initial funding on engineering and acquisition of senior AI-ML talent to ensure success and survival till the next round of funding. AI startups offer high salary packages to AI and ML experts, furthering the intense competition for top talent.

D. AI software is increasing at high rates

AI-driven software is rising at a high rate. Every aspect of the software, from design to development and deployment, is increasingly driven by AI. This means a reset of job roles, with hybrid positions that demand other technical skills. Ultimately this will lead to a growth in demand for AI and ML expertise.

E.  AI is steering the tech landscape and increasing jobs

The manufacturing and service sectors are getting disrupted by emerging technologies. Many jobs, such as quantum machine learning and AI-enabled cybersecurity, incorporating other tech, are leading to a rise in the demand for AI experts from across the spectrum.

F. Accelerated Research is driving job growth

Academic and institutional research in AI and ML are steering new job growth with their ingenious approaches.

Examples of AI research like machine learning safety and meta machine learning are making AI applications more ubiquitous and powerful.

Forward-looking research organizations are undertaking phenomenal research in AI.

OpenAi is one such non-profit research firm contributing to open-source modeling with free collaboration and research.

F. Job security

While the AI-ML salaries in a startup cannot compare with that of an MNC, another key criterion for AI practitioners to opt for an MNCs is job security.


The AI and ML job market is already witnessing steep growth with the future scope expanding every day.  The startup ecosystem is giving the MNCs a tough fight for a slice of the best talent in AI. Ultimately it depends upon your academics, certification path, hands-on experience with AI-ML models, the type of industry projects, and domain knowledge that will define your career prospects and salary packages.

As a beginner or a junior-level AI/ML engineer, you may like to begin with a startup where you work directly on AI-focused projects with innovators right from conceptualization to delivery. In an MNC, the core work in AI may have few variations unless you lead a project, and the learning curve is bound to flatten out quickly. Ultimately it is a trade-off between salary packages, research opportunities, and the learning curve.

Adnan Sarpal

hi, i am Adnan Sarpal Admin of 1k Sites.