Hire AI engineers: The ultimate step-by-step guide

According to a study conducted by StackOverflow in early 2022, demand for artificial intelligence (AI) software engineers is predicted to increase 54% over the next decade. Software developers with the necessary skills and expertise in AI may find this news exciting, as businesses will highly seek after them.

As a result, demand for AI talent has risen dramatically, making it increasingly difficult for businesses to identify and hire AI engineers. But don’t worry, you will find everything you need to know before hiring AI engineers in this blog. We will give you a closer look into an AI engineer’s roles and skills, and walk you through the process of hiring the best talents. 

So, buckle up and get ready to learn everything you need to know about hiring AI engineers!

Table of Content:

AI Engineers – Who are they?

An AI engineer is a professional responsible for designing, building, and testing AI models to help businesses implement and leverage artificial intelligence and machine learning technologies. AI engineers are well-versed in traditional software development, advanced data management, and the unique requirements of AI learning. They write complex algorithms that enable machines to learn from data and make informed decisions.

In addition to designing AI models, AI engineers also play a critical role in ensuring the smooth operation of AI and machine learning systems. They monitor these systems for potential issues, troubleshoot problems, and make necessary modifications to improve their performance. 

As AI technologies evolve, AI engineers must stay up-to-date with the new developments and continuously enhance their skillset to keep pace with the rapidly evolving industry.

What are the main roles and responsibilities of an AI engineer?

An AI engineer may be responsible for numerous tasks, here are some of them:

• Developing and maintaining AI development infrastructure and processes: AI engineers are in charge of creating and managing the AI development process as well as the infrastructure that supports it. This comprises programming languages, libraries, and frameworks, as well as other tools and technologies required to develop AI models.
• Build Infrastructure for Data Science: AI engineers play a critical role in ensuring that the development environments used to create AI products are easily reproducible and manageable after the final product is released.
• Developing and maintaining chatbots: Chatbots that interact with customers, delivering tailored assistance and boosting customer service, are created and maintained by AI engineers.
• Applying machine learning techniques for image recognition: AI engineers use machine learning techniques to develop models that can recognize images with high accuracy. This is essential for various applications, such as self-driving cars, facial recognition, and object detection.

• Using natural language processing techniques on text and voice transcripts: AI engineers use natural language processing (NLP) techniques to extract insights and analytics from text and voice data. This includes sentiment analysis, entity recognition, and topic modeling.
• Creating AI-powered solutions that mirror human behavior: AI engineers develop solutions that can mimic human behavior to accomplish repetitive tasks. This includes tasks such as data entry, image labeling, and content moderation.
• Making the machine learning process easier to understand: AI engineers develop APIs that simplify the machine learning process, enabling other business applications to interact with them and leverage their capabilities.
• Developing data pipelines: AI engineers develop data pipelines that streamline transforming raw data into the structured data necessary for AI processes. This involves tasks such as data cleaning, data transformation, and data integration.
• Developing recommendation engines for various applications, such as shopping sites, streaming services, and social media platforms. These engines use machine learning algorithms to provide personalized recommendations based on users’ preferences and behaviors.
• Collaborating with business owners and software development teams to identify business processes using AI, and develop strategies to implement these solutions.
• Undertaking problem-solving initiatives that involve utilizing logical reasoning, analyzing probabilities and statistics, and incorporating the latest machine-learning techniques.

Why do you need to hire AI engineers?

For companies that want to integrate AI into their operations, it can help them unlock potential benefits, such as:

• Introduce new practices and reinforce existing ones

Although AI is expected to eliminate certain jobs, it is worth noting that the phenomenon of job displacement has been occurring long before the advent of AI. 

However, the progress of technology has also given rise to new job opportunities such as AI-based agriculture services, app developers, among others. Rather than entirely replacing human workers, AI can be leveraged to augment their capabilities, enabling them to perform their duties more efficiently.

• Time savings

Hiring AI engineers can significantly improve the efficiency of your business operations. With the help of AI technology, time-consuming and repetitive tasks such as information gathering and consumer complaint filing can be automated, leading to faster and more accurate results. 

By automating hundreds of repetitive tasks, the time saved can be substantial. When software takes over manual tasks, the process time is significantly reduced, freeing up employees to focus on more creative and meaningful work.

• Keep up with technology trends

To stay competitive in today’s business landscape, it is essential to offer personalized customer service, leverage the latest technological advancements, and effectively manage large amounts of data. Hiring AI engineers can help you achieve these goals. 

As AI technology continues to advance, it’s expected to become an increasingly vital part of daily life and business operations. By hiring AI engineers early on, you can access the best talent and gain an advantage in understanding and integrating this cutting-edge technology into your operations.

How much to hire AI engineers?

The average cost of hiring AI engineers is expected to range from $100,000 to $200,000 annually, according to Glassdoor. 

The cost of hiring AI engineers can be relatively high due to the high demand for their skills. As per the U.S. Bureau of Labor Statistics, the job opportunities for all software developers, including AI engineers, are expected to increase by 22% over the next decade. This growth in demand is likely to drive salaries higher for AI engineers.

To hire AI engineers in the United States, you must pay them over $160,000 per year on average. In states like California, the average salary for AI engineers is close to $200,000. 

The hourly rates for AI developers can vary based on their experience and location. In the United States, the hourly rates for AI developers typically range between $75 to $150, which may be considered expensive compared to other parts of the world. In contrast, in India, the hourly rates for AI developers range between $50 to $75, which is more affordable in the market.

What are the core skills to look for when hiring AI engineers?

To thrive in their jobs, AI engineers employ a variety of technical and soft skills. Businesses should take the following core skills into consideration when they want to hire AI engineers.

Technical skills

• Programming skills

Advanced programming skills are essential for AI engineers to build and develop algorithms that can mimic human cognition. With these skills, AI engineers can identify coding errors and inefficiencies, leading to the creation of more effective programs.

Employers typically expect AI engineers to be proficient in programming languages (i.e., Python, Java, R, C++, and C#) as well as programming concepts like classes, data structures, and memory management.

• Advanced Mathematics

AI engineers also need to possess a deep understanding of mathematical concepts, including algorithm theory, quadratic programming, and partial differential equations. They need to have a strong grasp of statistics, including concepts such as means, standard deviations, and Gaussian distributions.

This knowledge enables AI engineers to work with complex models such as Naïve Bayes, Gaussian mixture models, and hidden Markov models. 

• Big Data technologies

AI engineers frequently deal with large datasets, which requires them to have a comprehensive understanding of big data technologies. Their knowledge of various big data technologies also enables them to adapt to the systems used by different clients and employers, ensuring seamless integration and optimal performance. 

With expertise in big data like Hadoop, Spark, and NoSQL databases, AI engineers can unlock the full potential of data-driven AI applications and deliver impactful results.

• Cloud platforms

As more businesses adopt cloud platforms for their software applications, including AI solutions, it’s important for AI engineers to have a comprehensive understanding of these platforms. By understanding leading cloud platforms like AWS, Azure, and Google Cloud, AI engineers can adapt to specific needs. 

• Deep learning and neural networks

A strong grasp of deep learning and neural networks is crucial for AI engineers to develop programs that are far more complex than what humans could code manually. These programs can be used for many apps, such as language translation, speech recognition, and image classification.

To excel in these areas, AI engineers require advanced knowledge of neural networks that go beyond basic single-layer models. 

• Algorithms and frameworks

AI engineers need to understand a range of machine learning algorithms, such as linear regression, Naïve Bayes, Support Vector Machine, and KNN. Additionally, their understanding of deep learning algorithms empowers them to build sophisticated AI models from unstructured data.

AI engineers are also required to have expertise in popular frameworks like TensorFlow, Keras, and PyTorch, which enables them to effectively implement these algorithms and build scalable AI solutions. 

Soft skills

• Communication skills

When looking for AI engineers, businesses should take their communication skills seriously, as they are extremely essential. AI engineers with strong communication skills can effectively collaborate with their team members and communicate ideas to project stakeholders. They have the ability to tailor their communication style to various audiences, adjusting the level of technical detail based on the specific needs of the listener.

• Problem-solving skills

To hire AI engineers, recruiters need to assess their problem-solving skills since working with artificial intelligence usually requires applying AI technology to solve complex problems. AI engineers need to have strong analytical skills to analyze problems and research relevant information, allowing them to develop effective solutions.

• Time-management skills

In the field of AI, meeting project milestones and deadlines is crucial for the success of any project. Therefore, businesses expect AI engineers to manage their time efficiently and allocate adequate time for critical activities. With strong time management skills, AI engineers can balance competing priorities and deliver projects on time and within budget.

• Collaboration skills

AI engineers are required to have strong collaboration skills, as they often work closely with other AI experts and IT professionals. These skills allow AI engineers to share their opinions and lilisteno the perspectives of their colleagues to arrive at effective solutions.

Where to hire AI engineers?

There are many ways to find and hire AI engineers for your business. Here are some suggestions:

• LinkedIn

When searching for AI engineers, LinkedIn remains the go-to platform for recruiters and hiring managers. LinkedIn Recruiter provides several search fields, including title, location, current organization, and years of experience, among others. By leveraging these search fields and creating boolean strings, recruiters can narrow down their search and find suitable candidates efficiently.

• Job boards

There are several job boards and online platforms that specialize in AI and machine learning job listings. They can include AI Job Board, AI Job Hunt, AI & ML Jobs, Kaggle, Careerbuilder, Upwork, Monster, Workable, SimplyHired, and more. Recruiters can leverage these platforms to access a diverse pool of AI professionals and find suitable candidates for their businesses.

• Outsourcing companies

Staffing companies such as Rocket, Robert Half, Randstad, and others can also be valuable resources for finding proficient AI engineers.  These companies specialize in identifying and recruiting top talent in the field of AI, providing a range of services to match candidates with job openings and assist with the hiring process. 

In addition to these companies, there are also several niche AI staffing agencies that focus specifically on AI and machine learning talent, such as BrainWorks, Talent500, and Harnham.

A step-by-step guide to hiring AI engineers

Hiring the best AI engineers for your business can be challenging, but don’t worry, we will provide you with a step-by-step guide so you will know exactly what to do during the hiring process. 

Define the role and the requirements

To hire AI engineers for your organization, it’s crucial to clearly define the skills, qualifications, and experience you are seeking in an AI engineer. Consider the specific needs of your business and the AI projects you are working on or planning to undertake to identify the specific expertise required. 

By outlining your requirements, you can attract candidates who possess the right skills and experience for the job, increasing the likelihood of a successful hire. Moreover, it helps to communicate your organization’s mission, culture, and values to ensure a good fit between the candidate and the organization.

Here are some questions you need to answer to clearly define the role:

• What levels of experience should the candidate have?
• What skills is the candidate required to have? 
• What are the main responsibilities of this role?
• What is your business’s budget for this role?

After outlining the requirements, start crafting a compelling job description for the role. It is necessary to specify the responsibilities, qualifications, industry experience, and tools the candidate will be working with. 

Launch your recruiting campaign

Once you have determined the requirements and budget for the AI developer role, it’s time to launch your hiring campaign. Start by posting the job opening on LinkedIn, job search sites like Monster, TheLadders, and Indeed, as well as on your company’s website and social profiles.

You can also hire freelance AI developers through portals like Upwork, Freelancer, and Toptal. And yet, you’ll have to track down a number of these freelancers before you discover one that is ready and able to meet your specific requirements.

Screen portfolios and select potential candidates

In this step, you need to work with your talent delivery team to set up an ideal screening process. This allows your team to identify candidates with the required skills and expertise that fit within your budget. You can narrow down the candidate pool by asking questions about their portfolio, approach to AI problems, and unique skills.

When evaluating AI engineer candidates, it’s important to consider their educational background, experience with previous AI projects, and proficiency in programming languages. Familiarity with machine learning algorithms and expertise with frameworks or libraries like TensorFlow or PyTorch are also important. 

Here are some questions you should ask yourself when evaluating candidates’ portfolios:

• Does this candidate possess the necessary hard and soft skills that align with the requirements of the AI engineer role?
• Do we share similar values and principles about designing and delivering high-quality AI products or services?
• Does this candidate fit well with our team’s culture and values, as well as our product or service goals?
• Is this candidate open-minded and receptive to learning from others on the team?
• Is this candidate highly motivated to succeed and excel in their role, and do they exhibit a strong work ethic?
• Does this candidate have a passion for innovation and AI development, as evidenced by their past projects and experiences?

Conduct an interview

Once you shortlist the potential candidates, you can schedule an interview with them to assess their skills and knowledge. During the interview process, it’s essential to ask questions about the candidate’s experience in AI development, their proficiency in machine learning techniques, and their ability to handle large datasets. 

By probing into these areas, you can assess the candidate’s technical skills and expertise, as well as their ability to work with the specific AI technologies and tools required for the projects.

As a way to evaluate a candidate’s technical abilities and problem-solving skills, consider asking them to perform a test. This test may be a simple programming exercise related to your product or service. This can help you assess the candidate’s problem-solving skills, while also giving them a better understanding of your company’s goals. 

By providing a hands-on exercise, you can gain valuable insights into the candidate’s coding skills and assess how they approach problem-solving in a real-world context.

Make an offer & sign a contract 

When you identify the right AI engineers that best match the requirements for the project, it’s time to close the deal. 

When making a job offer to a top AI candidate, it’s important to provide a competitive salary, comprehensive benefits, and any additional perks that may be attractive to the candidate. By offering a competitive package, you can demonstrate your organization’s commitment to retaining top AI talent. This can increase the likelihood of a successful hire.

Additionally, it’s important to have a detailed contract in place that outlines the payment scheme, terms of the agreement, and required deliverables. 

Onboard the new hire

After the AI engineer accepts the job offer, it’s necessary to ensure a smooth onboarding process by the leader. In this step, you can provide all necessary documentation, and access to tools and resources, and introduce them to the team. 

This helps the new hire acclimate to their role and the organization quickly. To facilitate their integration, consider assigning a mentor or buddy who can help them understand the organization’s processes, ongoing projects, and provide guidance when needed.

Wrapping up

As the AI field continues to grow and dominate the job market across all industries, the demand for talented AI engineers is higher than ever. The top companies across various sectors are actively seeking talented AI engineers with demonstrable experience and expertise in the field. To hire AI engineers, businesses should take a look at the comprehensive guide provided in this blog. By investing in AI talent, businesses can stay ahead of the curve and leverage AI technology to gain a competitive advantage.