How to hire AI developers? Know the process

We see artificial intelligence everywhere, be it ChatGPT, Dall-E, and many other AI-based tools. With artificial intelligence, it is now possible to create articles, art, audio, etc., in a few clicks. They are evolving by overcoming limitations in creativity and knowledge work. 

As per a report conducted by McKinsey, AI will bring $13 trillion to the global economy by 2030.

If you are looking to hire AI developers in 2023 but don’t know the exact process, you can take help from our guide. This guide covers the full process: writing a compelling job description, interview questions, developer title, etc.

Demand for AI engineers in 2023

Machine learning has contributed to industries from finance to medicine, transportation to education.

Artificial intelligence has multiple use cases, be it writing codes, detecting financial fraud, directing autonomous vehicles, and diagnosing patients from MRI images.

Technologies based on AI and ML are redefining the ecosystem for data, infrastructure, and applications for various complex projects.

But the main challenge for companies is to hire qualified developers, as the availability of skilled developers is extremely small. 

With the right techniques, as discussed in the blog, you can maximize the chances of finding and hiring the best developers for your project.

What do AI developers do?

Many tech companies use technologies based on machine learning to advance their projects by automating processes or scaling business operations. 

Developers at these companies are strong programmers with additional expertise in tuning parameters, selecting activation functions, and designing networks. 

Most artificial intelligence professionals focus on research and development, especially for building applications that stimulate human intelligence.

To ensure the success of your development project, ensure your team structure is on the right track.

What is the structure of an AI development team?

A successful AI development team should consist of the following team set:

1. Data team

This team is responsible for processing and analyzing the data. Typically, the data team will include the following professionals:

• Data scientist 
• Data engineer 
• Machine learning engineers 

2. Algorithm/Research team

The team aims to explore new ways of solving business problems by developing specific automation-based algorithms. List of required professionals in the algorithm team:

• Deep learning engineers
• Machine learning engineers
• Computer vision engineers
• Natural language processing researchers

3. Infrastructure/Platform team

The team will build, maintain and scale the software product. The  platform team consists of the following members:

• Back-end engineers
• Infrastructure engineers
• Dev OPS engineers 
• Platform engineers
• Site reliability engineers
• System engineers
• Security engineers

4. Application team

The team is responsible for creating an app or product through which your customer will interact with. Team members will include

• Front end engineers
• Full stack engineers
• UI/UX designers
• Product managers 

The required skill set of AI developers 

It would be best to have the following skill set for a suitable machine learning developer. 

I. Knowledge of artificial intelligence and machine learning 

AI is a complex and newly emerging field having many types and subsets. There is a strong requirement for developers to have a solid understanding of concepts and a theoretical understanding of artificial intelligence and machine learning. 

1. Deep learning

Deep learning creates artificial neural networks that can train models and solve complex problems. These neural networks are inspired by the functioning and structure of human brains that contain layering, complexity, and abstractions. 

Deep learning involves different training models, such as supervised, unsupervised, and reinforced learning. Deep learning allows networks to learn and improve independently.

Some real-world examples of deep learning include the Tesla Autopilot system, Spotify, Amazon recommendation system, Google, DallE, and ChatGPT.

2. Computer vision 

This technology enables computers to see and understand visual data such as images and videos. Computer vision utilizes large data sets to help computers understand images, recognize faces, track emotions, and make sense of visual information.

3. Natural language processing

NLP combines linguistics encoding to allow computers to understand the interpretation right human language. Which e-mail categorization, translation, chatbots, or some examples of natural language processing.

NLP can also transform unstructured data into structured data to make it readable for machines. 

II. Programming languages

Most development job involves coding and data engineering. Therefore, it becomes essential for you to hire developers with strong coding skills in any of the following programming languages.

1. Python 

Python is a widely used high-level programming language in machine learning and artificial intelligence. The programming language consists of many libraries and frameworks such as Tensorflow, Pytorch, and sci-kit-learn, making it an easier way for a developer to implement machine learning models.

2. C/C++

A low-level programming language that is often used for computationally intensive tasks or building systems when performance is critical.

3. Java/Scala

A programming language mostly used by enterprise applications for enabling large-scale software development and distributed system. Java and Scala are associated with big data that is less relevant to many applications based on artificial intelligence. 

4. Swift and Javascript 

For building AI applications for mobile devices, Swift and Javascript are popular mobile languages for programming artificial intelligence-based products. 

5. Julia

Similar to Python, Julia is a high-level programming language that gains its popularity in the domain of automation.

6. R

R is a programming language widely used for data analysis and contains several libraries and frameworks such as caret, random-forest, and caret. Moreover, R is the most suitable programming language for statistical computing and visualization.

III. Familiarity with the tech stack

Developers having expertise in the following tools, libraries, frameworks, and concepts would be best for your team. 

Expertise	Tech Stack
DL Frameworks	PyTorch, MXNet, Nvidia Caffe, Caffe2, Chainer, Theano
Modules/Toolkit	Microsoft Cognitive Toolkit, Core ML, Kurento’s computer vision module
Libraries	OpenNN, Neuroph, Sonnet, Tensorlfow, Tensor2Tensor,  tf-slim
Algorithms	Supervised/unsupervised learning, Clustering (density-based Hierarchical, partitioning), Metric learning, Few-shot learning
Neural Networks	CNN, RNN, Representation learning, Manifold learning, Variational autoencoders, Bayesian networks, Autoregressive networks

IV. Problem-solving skills

Developing complex algorithms need excellent problem-solving skills. The problems and challenges involved in automation development might be technical. Therefore, with the right problem-solving skills, developers can develop better solutions for your project. 

Role of artificial intelligence in different industries

The role of automation in different industries is given below:

I. Finance and Fintech

• Detection of fraudulent transactions
• Credit scoring, risk assessment, and underwriting
• Personalized financial advice 
• Portfolio management
• Algo trading

II. Healthcare 

• Analysis of medical imaging for anomaly identification and diagnosis
• Drug discovery (prediction of protein structure), design, and testing of genetic data 
• Predictive analytics and electronic health records (EHR)

II. Marketing  

• Customer behavior and purchase trends predicting (time series forecasting)
• Ad targeting and personalized marketing strategies
• Customer engagement enhancement

III. Transportation

• Traffic forecasting
• Autonomous vehicles
• Schedule and route optimization in real-time

IV. Customer support and retail

• Virtual assistants and chatboxes (speech recognition) 
• Personalized recommendation systems
• Inventory control and price optimization
• Customer review sentiment analysis

V. Manufacturing

• Robots controlled by artificial intelligence and robotic control systems
• Quality assurance and predictive maintenance
• Supply chain management, logistics, and warehousing

VI. Gaming

• NPCs and game combatants controlled by AI
• Dynamic game difficulty balance and player experience modeling
• User behavior data mining and monetization

VII. Supply chains

• Warehouse Automation
• Logistics processes

VIII. Finance

• Automated report generation
• Tracking bills 

Know the common job title and their roles in automation development.

Job titles for AI developers

These are the common job roles for developers that will be responsible for giving separate contributions to your project. Let’s explore job roles involved in building automation-based products. 

I. Machine learning engineers

ML Engineers work with data scientists and software engineers to integrate machine learning models into systems. They built AI and ML models and the necessary infrastructure to train and deploy them.

• Common languages: C, C++, Python, Java
• Common frameworks: PyTorch, Keras, TensorFlow, sci-kit-learn

II. Data scientist

They are part mathematicians, part statisticians, and coders. Data scientists take a vast amount of noisy data, whether structured or unstructured, and build models to extract information from meaningful conclusions.

Data Scientists may use automation to create models that generate predictions and guide decision-making.

• Programming languages: Python, R, SQL
• Databases: PostgreSQL, MySQL, / NoSQL databases: (MongoDB, Redis, CouchDB)
• Data Visualization tools: Sisense, Excel, Tableau, Power BI,

What’s the difference between a Data scientist and an ML engineer? 

Typically Data Scientists focus on the models themselves and finding the information they need to determine technical solutions to problems. When the solution is already decided, and implementation and scalability are the critical issues, Machine Learning Engineers put the models into production and fit them into restricted computational resources. 

III. Machine learning scientist

The job role of ML typically involves creating algorithms, researching ML techniques, and building and optimizing machine learning models. They have completed degrees in computer science, data science, statistics, mathematics, etc. 

• Common languages: C, C++, Python
• Common frameworks: PyTorch, Keras, TensorFlow, sci-kit-learn

What’s the difference between an ML scientist and a data scientist? 

Data scientists focus more on extracting insights from data and making data-based decisions. While machine learning scientists tend to be more research-oriented and more concerned with ML models.

IV. Data engineer

Data engineers build the infrastructure necessary to process and access data. They build virtual “pipelines” between data systems, allowing data scientists to access this data for analytical or operational purposes.

• Common languages: Python, Java, Scala
• Common areas of focus: Extract, transform, and load (ETL) pipelines, data infrastructure, data processing, data ingestion, data streaming
• Common big data technologies: Spark, Storm, Hive, Flink, Hadoop

What’s the difference between an ML Engineer and a data engineer? 

The duties of a data engineer typically include focusing on converting data into usable models or designing and building the infrastructure to put ML models into production.

Understand the process of hiring developers for your project.

How to hire AI developers?

You can find and hire developers with the right qualifications with our step-by-step guide.

1. Define the skills needed for your company

Before companies start searching for ideal candidates, they first need to define what they are exactly looking for. By outlining the required skills for your project, you can post a specific job role for hiring developers.

Moreover, crafting the persona of your candidate will help you to understand what you are searching for, their motivations, and how to craft pitches to encourage them to join your firm. For example

Persona name	Job Title
Education	Company Experience
Years of Work Experience	Skills
Salary Range	Goals
Values	Pain Points

2. Know how to find AI developers

There are multiple options available you can consider for hiring developers for your team.

I. In-House recruiter

Pros:

Hiring in-house developers will enable them to be familiar with the culture of your company; plus, they may have a deeper understanding of how to be successful in your specific roles. 

With the biggest tech layoff throughout the past years, there is a high possibility that you will get highly skilled developers for your project.

Cons: 

There is a requirement for higher upfront costs and effort. Moreover, during economic uncertainty, you need to be consistent in paying for full-time in-house developers. 

Tips:

 Consider the following ways to hire engineers 

• Host a competition on Kaggle, an open-source machine learning and data science community. 
• Search medium tags such as artificial intelligence to find experts for your team.
• Visit sites like GitHub and Stack Overflow to find the best engineers by checking their uploaded projects. 
• Check out the work and projects done at AI conferences. 

II. Freelance or Contract recruiter

Pros: 

If you don’t need developers long-term, then hiring freelance developers would be a great option.

Cons: 

Likewise, developers in agencies, freelancers, and contract recruiters aren’t screened and may lack the technical skills and knowledge required for your project. 

Additionally, sometimes their hourly rates may go beyond $75-150 per hour.

Tips: 

You can visit some popular sites like Topal and Upwork to hire freelancers.

III. Recruiting agencies

Pros:

This agency aims to employ experienced developers with technical knowledge. Plus, they have great experience in finding ideal candidates for specific projects, as the compensation is based on results. 

Cons: 

Recruiting agencies may involve high fees that can be up to 15 to 20% of the candidate’s first-year salary or even more. 

Sometimes unqualified agencies may waste your time by flooding you with non-experienced and unskilled engineers.

Tips: 

Finding agencies that specialize in filling job roles based on automation development would definitely be helpful for you. You can find the best agencies by checking their screening process and tracking records of hiring the best developers for their other clients.

IV. Contract developers

Pros:

Hiring developers on a contract basis gives flexibility during uncertain economic conditions when you don’t need developers for a long period of time.

Cons:

Contract developers don’t have enough work experience due to having fewer opportunities to work on high-impact and sustainable projects.

Tips:

Visit top candidate sourcing websites such as Turing, Apollo Technical, and Candidate Labs for hiring developers on a freelance basis or basis

V. Outsourcing to hire artificial intelligence engineers

Pros:

You can free yourself from engaging your candidates, as outsourcing will enable you to automate candidate-job matching and outreach.

Additionally, they offer the most flexible options based on your recruiting needs and budget to streamline your development project even further. 

Cons:

You may have to engage yourself to learn new sourcing tools.

Tips:

If you need that bandwidth, services like Idea Usher can help. You can get a free consultation call and the best solutions for your project from their experts.

3. Learn to write a job description

The best job descriptions will help you to grab the attention of engineers, giving them a compelling reason to consider your opportunity. 

When writing a job description, you can highlight a few points, including

• Company’s description: Tell them about your business and company’s goals that you think can be achieved by hiring developers
• Innovative tech stack: Most developers will love to get into a job that implements the usage of the latest and coolest technologies which can help them to advance their careers even further.
• Exciting new opportunities and responsibilities: Many developers will be excited to join your company if you tell them in detail about new opportunities and responsibilities when they join your company. Plus, developers will be excited to take ownership and lead features end-to-end.
• Perks and benefits: You can offer many perks and benefits, including flexible working hours, tuition assistance, wellness programs, etc., to attract your ideal candidates for the job profile. Moreover, offering remote opportunities will help you attract talented developers across the country, giving you a better competitive edge for your project.

4. Read resumes and check past projects

We understand there are a lot of challenges involved in reading the resumes of developers, as their resumes might be dense with technical terms and jargon.

However, you can select the best candidate for your project by evaluating their experience in past projects. Checking their portfolio will help you Identify their skills and experience and will enable you to find and select the best one for your project.

5. Write a compelling outreach message

Even after the economic uncertainty, the demand for engineers in automation will still grow. When most of the artificial intelligent engineers you wish to hire are already employed, The only great option is to reach out and start pitching.

You can refine your pitch with the given key points:

Subject line: On average, the tech worker receives 121 emails a day. Therefore it becomes essential for you to start pitching from a subject line, including personalizing them with names of potential candidates, including quick pitch points.

Personalization: To stand out from the rest of the emails, you can personalize them, explaining why you find the skills of potential candidates are relevant to the role and how their domain expertise is a good match for your project. 

Compliment: You can leave a positive impression on your candidate by highlighting strengths in their background, such as educational history, work at selected companies’ awards, etc.

Follow-up: It’s definitely worth sending a follow-up, as about 2/3 of candidate replies come from follow-up emails. However, to avoid harming your company brand, you need to avoid excessive follow-ups.

6. Look for soft skills

Besides strong programming skills and familiarity with artificial intelligence technology, your ideal candidate should have the following soft skills:

Motivation to learn and grow: The motivated developers are mostly involved in side projects and engage in forums and side projects related to automation development. 

The developers mostly engaged in activities related to artificial intelligence development are eager to learn and grow their careers.

Communication skills: Having great communication skills will enable developers to break down technical concepts into clear and understandable topics. 

Good communication skills will enable developers to explain their technical projects to non-technical audiences. 

Basic understanding of how the business operates: The developers’ basic understanding of how businesses operate and generate revenue and popular use cases will enable you to leverage their skills for your business. 

Critical thinking: Developers must tackle new challenges involved in product development. With great problem-solving skills, developers can generate, analyze, and evaluate various creative solutions for your business.

Ability to invent new approaches: Developers having a strong mindset for taking risks and refusing to give up in the face of uncertainty can be a plus point to make them an ideal candidate for your team.

7. Know the interview questions. 

You can use the following questions to evaluate the technical skills and expertise of a developer:

• Tell me about projects you’re most proud of, from ideation to implementation. What was your approach, and what was the result of that project?
• What methods can be used to improve the performance of an ML model?
• Currently, how are you advancing and improving your knowledge and skills?
• How would you approach designing a product recommendation system?
• What artificial intelligence-based product impressed you the most?
• In which way do you handle unbalanced data?
• When would you use weak versus strong AI?
• What is your development approach for building a language model with a small data set?
• How do you determine whether a problem is ML solvable?
• Can you mention some technical challenges in artificial intelligence in 2023? 
• Tell me about the challenges you’ve overcome in implementing automation-based technologies.

How to identify the perfect candidate for AI development?

You can ask yourself the following questions to identify whether the candidate would fit your project:

• Does the candidate have the required soft and hard skills?
• Is the candidate share similar values regarding making good products or services?
• Can this candidate collaborate well with my team to achieve common goals?
• Are they a good cultural fit for my team and our product/service?
• Is the candidate motivated and valuable to contribute best to my company?
• Does this candidate have a passion for programming and innovation? And what are their contributions to the past projects?

Conclusion

Hiring skilled and experience AI developers is the best way to ensure the successful development of your artificial intelligence-based project. 

We recommend outsourcing your project to an AI development company as they are experienced in building and delivering high-quality AI-based products across multiple industries.

Also, with outsourcing, you can free yourself from the hiring process to screen and select the best candidate for your project.

How can Idea Usher help?

If you are looking for an AI development company to help you with market research to launch your product to your target market, you can contact Idea Usher.

We are a team of AI developers having experience in AI development across multiple industries. We use the latest technologies and best practices to ensure your product is secure, scalable, and user-friendly.

Contact us today to learn more about how we can help you unlock the full potential of your AI-based product. 

Contact Idea Usher 

Email:

[email protected]

Phone:

(+1)732 962 4560

(+91)859 140 7140

FAQ

1. How do I hire an AI engineer?

You can follow the given steps to hire developers:

• Define the skill set needed for your company
• Know how to find AI developers
• Write a compelling job description
• Read the resumes and check the past projects and portfolios of your candidates
• Look for soft skills required for your team
• Know and ask the set of interview questions to hire the best one for your team

2. What are good questions to ask about artificial intelligence?

You can ask the following questions:

• Which artificial intelligence-based product most impressed you?
• How do you deal with uneven data?
• When do you prefer weak versus powerful AI?
• What is your technique for developing a language model with a tiny data set?
• How can you know if an issue is ML solvable?
• Can you list some of the technological hurdles that artificial intelligence will face in 2023?
• What strategies may be utilized to increase an ML model’s performance?
• How are you currently progressing and strengthening your knowledge and skills?

3. What are the roles of AI developers?

The job roles are as follows: 

• Software designing 
• Building data science infrastructure
• Data Analytics 
• Natural Language Processing
• Creation and deployment of AI algorithms 
• Image Processing