Myn and AI: Revolutionising Recruitment with Cutting-Edge Technology

Myn and AI: Revolutionising Recruitment with Cutting-Edge Technology

From its very inception, Myn has been developed as an AI-first product, embedding Machine Learning (ML) and AI at its core. While the world has gone crazy over generative AI, it's important to remember that Machine Learning and AI have been fundamental to Myn's development long before the advent of ChatGPT.

Myn's Strong Focus on AI

At Myn, we recognise that AI isn't just a buzzword; it's a constantly evolving technological frontier. We are strategically positioned to leverage these advancements, understanding that the open nature of AI development allows any company with the right technical skills and data to participate.

The Myn network itself provides an incredible source of data for AI, and combined with our strong network effects, modern AI algorithms can quickly map out opportunities, and help streamline a companies talent acquisition.

Personalisation Through AI

For too long, candidates have faced a frustrating lack of personalised attention in the recruitment process. Recruiters are often stretched thin, leaving many applications unanswered. Myn is changing this.

Our AI understands market dynamics and can provide individuals with valuable career path guidance. Imagine an intelligent, AI-powered agent for every person, possessing a deep understanding of occupations, skills, and the job market, capable of analysing career options and enabling optimal career decisions. This is the future Myn is building.

How Myn Uses AI: A Deeper Dive

Here are just a few of the ways we are currently employing Machine Learning and AI here at Myn:

• Bespoke Text Embedding Model: Perhaps the most fundamental aspect of the AI technology that we use, is a bespoke text embedding model that has been specifically developed for use in recruitment. Embedding models allow us to create a numerical representation of text and using this numerical representation determine how similar two pieces of text are, this in turn allows us to effectively, efficiently and economically match candidates to vacancies at speed and at scale. There are numerous pre-trained Embedding models trained on extremely large data sets that have been made publicly available. However, we found that these, while interesting, were not really suitable for our purposes, so we set about learning our own set of embedding vectors specifically tailored to the domain of recruitment. Our Embedding Models have been trained on 4 billion words from more than 100 million Candidate Profiles and Job Descriptions allowing it to capture the nuances of how language is used in the world of work.
  
  
• AI-Powered Summarisation: We also use AI to summarise vacancies and candidate profiles in terms of automatically generated skill groups that describe the skills required to perform a given role. This allows us to provide a more fine-grained explanation as to why we think someone is a good fit for a given vacancy.
  
  
• Job Function Classification: Another way we are using AI is to tackle the problem of Recruitment Professionals needing a better understanding of the people that they already have information on or access to that are stored in Applicant Tracking Systems (ATS) and databases. While Boolean search has historically been used to interrogate these systems, finding all of the different ways that people use to describe their job titles makes this a difficult task. Our solution to this problem is to train a job function classifier to predict a job function based on the work description. Standardising job titles to a fixed set of occupations allows insights into the sort of candidates that are stored in these systems.
  
  
• Generative AI Exploration: Then of course there is Generative AI. No discussion of AI can ignore the impact that ChatGPT and its competitors have had in the last couple of years. Like, what seems like most of the world, we have ridden the wave of excitement and begun to start using these powerful new tools for among other things; extracting structured information from unstructured text, rewriting vacancies in a standardised style, classifying jobs into the ONET (Occupational Information Network) taxonomy as well as exploring many other areas where we see potential for this technology to be applied. While in many cases it is easy to create a compelling proof of concept using generative AI, it is much harder to create something that works consistently and does not suffer from hallucinations (confabulations that look sensible but are in fact not true) as such we are treading carefully in this space. As these technologies mature, as an AI company at its core, Myn are well placed to take advantage of them.

Since almost all of our machine learning models are developed in-house we have no dependence on third party software and, as such, we are able to have complete control over deployment and costs.

The Future is Intelligent

At Myn, we're not just keeping pace with AI advancements; we're actively shaping them. We are committed to building practical, reliable AI solutions that address real-world recruitment challenges.

In conclusion, at Myn, we're at the cutting edge of AI and Machine Learning, revolutionising the employment landscape. We're excited to have you join us in this journey towards a more efficient and effective Future of Work.