What is Artificial Intelligence and Who is an AI Engineer
Artificial intelligence (AI) engineering is the process where algorithms are used to develop AI-based applications. Artificial intelligence refers to machines performing tasks typically done by human beings.
An artificial intelligence engineer uses AI to develop apps that help businesses boost efficiency and productivity.
How to Hire Artificial Intelligence Engineer
To hire artificial intelligence engineer, write a job description and post the vacancy on a tech hiring platform. Assess the basic skill sets of the engineer. You would also have to evaluate their educational background and work experience. Further, you would have to conduct a skill assessment test. Follow this up by interviewing the candidate.
Factors to Consider Before You Hire Artificial Intelligence Engineer
Before you hire artificial intelligence engineer, understand the scope of your project. Assess if you need a long-term or short-term hire. Further, consider if you need an entry-level, mid-level or senior-level engineer.
Assess your client base – what industries do they belong to? Your artificial intelligence engineer should be familiar with a range of industries. They should understand the needs of the end-user. For instance, developing an AI app for retail or e-commerce may be different from building AI apps for health care.
Understand the trends in AI engineering. For example, the metaverse has emerged as a key trend. Metaverse is a virtual world where users can work and play in an immersive space. Awareness of trends helps you in the hiring process.
Skills to Keep in Mind When You Hire Top Artificial Intelligence Engineer
Programming Languages
Hire top artificial intelligence engineer who understands programming languages like Python and Java. Python offers libraries and pre-set packages for low code. It runs on multiple platforms too. These features are useful while building AI models. Java offers easily codable algorithms for building AI models.
Frameworks like TensorFlow, Keras
Tensorflow is an open-source library for AI. It is Python-friendly and is used for a range of ML-related tasks. Keras is another library offering a Python interface. It is useful for building AI-based models.
Neural Networks
Neural networks are sets of algorithms that are aimed at identifying patterns. CNN stands for convolution neural networks while RNN stands for recurrent neural networks. RNN interprets sequential data like stock prices or temperature. CNN is used in image recognition. Knowledge of which neural network to use for a project is essential.
Cloud Platforms
Understanding of cloud platforms such as MS Azure, Amazon AWS and Google Cloud is good to have. These platforms help you scale and deploy AI models.
Agile and Scrum
Agile and Scrum are software development methods. Agile involves constant feedback and improvement at every stage of the development lifecycle. Scrum is one of the Agile frameworks that focus on teamwork.
Big Data Technologies
Knowledge of big data technologies like MongoDB, Hadoop or Spark is good to have. MongoDB is a key NoSQL database management program. It is used for working with big sets of distributed data. It is used for caching in real time, product-based apps and content management systems. Hadoop and Spark, developed by Apache, find uses in big data analytics.
Concepts of Linear Algebra and Probability
Knowledge of concepts like linear algebra and probability is important. Linear algebra is a branch of mathematics that involves linear combinations. It involves columns of numbers called vectors and arrays of numbers called matrices. Probability means the likelihood of an event. It lies between 0 and 1. This theory is used in machine learning, a branch of AI. Machine learning involves prediction of outcomes on the basis of data.
Soft Skills
Soft skills like problem-solving and communication skills are important. Also, the artificial intelligence engineer should have an eye for detail.
Steps to Hire Artificial Intelligence Engineer
Create a job description outlining the roles and responsibilities of the artificial intelligence engineer. Some of them may include:
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Turn ML models into application program interfaces so that other apps can use them.
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Create AI models from scratch
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Build infrastructure to transform data and automate it for use by data scientists
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Conduct statistical analysis and finetune results that help decision-making
Screen candidate resumes and assess educational qualifications and skill sets. Look for the right match for your business needs.
Conduct a skill assessment test for a set timeframe. The test helps you assess the candidate’s understanding of skills like big data.
Interview candidates you have shortlisted after the test. Assess their technical and soft skills before you decide to hire.
If you have decided to hire a candidate, send out an offer letter, stating terms of employment and salary structure.
How to Identify Reliable and Experienced Artificial Intelligence Engineer
Ask for references from previous employers. Talk to the references to understand how reliable the artificial intelligence engineer is, in terms of delivering projects on time. Also, find out about the candidate’s interpersonal skills and ability to lead a team.
Ask for the engineer’s portfolio of work. Judge the quality of work and the number of projects the engineer has worked on.
Evaluate the artificial intelligence engineer’s career path. Assess how committed they are to the field of AI engineering.
