AI talent recruitment challenges in Enterprises

recruitment ai developers

Hiring AI Developers in Enterprises

According to McKinsey, generative AI is a key driver of productivity in the modern economy, radically transforming how businesses operate and compete [1].

According to an additional report by LinkedIn, the role of AI specialist ranks as the #1 emerging job, highlighting the growing demand for AI expertise in various industries. This surge in demand is prompting companies to invest significantly in employee training and development to fill AI roles, emphasizing the critical need for AI developers in the current job market.

Furthermore, a majority of respondents in a McKinsey survey reported difficulty in hiring for each AI-related role in the past year, indicating a significant gap in the availability of skilled AI professionals [4]. This gap presents a clear opportunity for enterprises to focus on hiring and nurturing AI talent to meet their evolving technological needs.

ai roles

The visualization above represents the challenges faced by enterprises in recruiting AI talent, based on a McKinsey survey. It shows that a significant majority (60%) of respondents reported difficulty in hiring for AI-related roles in the past year. This disparity underscores the need for enterprises to focus more on hiring and nurturing AI talent to meet their evolving technological requirements.

According to Deloitte, team augmentation with AI developers is an essential strategy for businesses looking to stay ahead [3]. It involves not just expanding the workforce but enriching it with specialized skills and new perspectives. This approach is particularly beneficial in tackling complex AI projects and fostering innovation. Vstorm stands at the forefront of this change, offering unmatched expertise in recruiting top AI talent.

Key AI roles recruitment

1) Machine Learning Engineers

The role of Machine Learning Engineers has become increasingly pivotal in the modern business landscape. These professionals specialize in developing algorithms and models that enable machines to learn and make decisions with minimal human intervention. Their expertise is crucial in a variety of sectors, from finance to healthcare, where they contribute to enhancing efficiency, automating repetitive tasks, and deriving insights from large datasets.

Key roles and responsibilities

  • Developing Machine Learning models: ML Engineers are responsible for creating advanced models that can process and analyze large amounts of data efficiently.
  • Data analysis and interpretation: They possess strong analytical skills to extract meaningful insights from data, which are essential for strategic decision-making [4].
  • Automating data-driven processes: Machine learning engineers design systems that automate tasks, reducing the need for manual intervention and improving operational efficiency.

In summary, hiring Machine Learning Engineers is a strategic move for businesses aiming to make the best of  AI and data analytics to drive growth, innovation, and efficiency.

2) Data Science Specialists

Data Science Specialists are at the forefront of extracting valuable insights from vast datasets. Their expertise in data mining, interpretation, and analysis is invaluable in informing business strategies and operational improvements.. This role involves a blend of statistical analysis, machine learning, and data visualization to extract meaningful insights from vast datasets. These insights are crucial for strategic decision-making across various industries.

Core functions of Data Science Specialists

  • Statistical analysis and predictive modeling: They utilize statistical techniques to interpret data, identify trends, and make predictions about future occurrences.
  • Machine Learning implementation: Data Science Specialists apply machine learning algorithms to automate data analysis and create predictive models, enhancing business operations and customer experiences.
  • Data visualization and communication: These professionals are adept at presenting complex data in an understandable format, making it easier for stakeholders to grasp insights and make informed decision

3) AI Programmers and Developers

Programmers and developers with AI expertise, particularly LLM (Large Language Model) Engineers and NLP (Natural Language Processing) Engineers are the architects behind the development of intelligent systems that can understand, interpret, and generate human language.

Roles and significance of AI Programmers

  • LLM Engineers: These professionals specialize in building and refining large language models that can process vast amounts of text data. They work on cutting-edge technologies like chatbots, virtual assistants, and other AI-driven applications that require a deep understanding of human language [1].
  • NLP Engineers: NLP Engineers focus on developing algorithms that enable machines to understand and respond to human language in a way that is both meaningful and contextually relevant. Their work is crucial in areas like sentiment analysis, text classification, and language translation [5].

Impact on business and innovation

  • Enhanced customer interaction: AI programmers develop systems that improve customer engagement through more natural and efficient communication.
  • Data analysis and insight generation: Their expertise allows for the extraction of valuable insights from unstructured data, aiding in data-driven decision making.
  • Automation of repetitive tasks: By automating language-based tasks, these engineers significantly increase operational efficiency.

4) Comparison of roles

The visualization below provides a comparative overview of three key roles in the field of AI and data science: Machine Learning Engineers, Data Science Specialists, and AI Developers (including NLP and LLM Engineers). The comparison is based on a relevance scale from 1 to 5 across various skills and competencies:

comparison roles
comparison roles
  • Algorithm development: Machine Learning Engineers are highly focused on this, as are AI Developers, while Data Science Specialists also engage significantly in this area.
  • Data analysis: Data Science Specialists lead in this skill, with Machine Learning Engineers also showing strong involvement.
  • Predictive modeling: Machine Learning Engineers and Data Science Specialists both show high relevance in this area.
  • Natural Language Processing (NLP): This is a key area for AI Developers, particularly those specializing in NLP and LLM.
  • AI system integration: AI Developers, especially those working with NLP and LLM, are highly involved in integrating AI systems, more so than the other two roles.

This tool can be particularly useful for HR managers and clients in understanding the distinct roles and skill sets of these professionals in the AI industry.

The AI Developers’ recruitment process

The recruitment process of AI developers, as conducted by Vstorm, is a comprehensive and strategic approach that not only focuses on talent sourcing and acquisition but also extends to payroll and retention. This approach, particularly when it comes to outsourcing recruitment and hiring AI developers as consultants, offers several key benefits to businesses.

Outsourcing AI projects, including the recruitment of AI professionals, has been shown to be highly beneficial for businesses. One of the primary advantages is cost efficiency. By outsourcing, companies can reduce expenses related to recruitment and infrastructure. This is particularly relevant in the context of AI projects, where the need for specialized skills is paramount, and the cost of developing such expertise in-house can be substantial [1].

Moreover, outsourcing recruitment allows companies to tap into a larger pool of talent and expertise, which is especially crucial in the field of AI where specialized skills are in high demand. This not only enhances the quality of recruitment but also accelerates the hiring process, allowing businesses to quickly adapt to market changes and technological advancements [2]. Furthermore, companies that outsource recruitment can also benefit from the experience and expertise of recruitment agencies like Vstorm, which specialize in identifying and attracting top AI talent.

In addition to talent acquisition, Vstorm’s comprehensive approach to recruitment also includes managing payroll and retention, ensuring that the talent not only matches the company’s needs but also remains engaged and productive over the long term. This holistic approach to recruitment and retention is a key factor in the success of businesses in the rapidly evolving AI landscape.

Overall, the strategic decision to outsource the recruitment of AI developers and manage their payroll and retention can lead to significant benefits for businesses, including cost savings, access to specialized talent, and improved efficiency in the recruitment process.

Expertise in AI developers’ recruitment

A proven track record

Vstorm’s experience in the field has established them as a trusted partner for numerous corporations in securing the best AI talent. Their recruitment process is not just about filling positions, but about creating value for their clients. Our team keeps abreast of the latest trends in AI and machine learning, ensuring that the developers they recruit are not only skilled but also forward-thinking and innovative.

The AI talent recruitment is no longer just a trend but a necessity for businesses looking to thrive in a technology-driven market. Vstorm provides an invaluable service by not only finding the right talent but also aligning them with the strategic goals of their corporate clients.


  1. – The state of AI in 2022—and a half decade in review
  2. – The state of AI in 2023: Generative AI’s breakout year
Jagoda Malanin
Jagoda Malanin
Marketing Manager
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