The artificial intelligence (AI) development market is booming, and it’s not just because of the rise of chatbots and autonomous systems. AI developers are in great demand and this will continue in the future as AI gains importance. More companies and industries are hiring artificial intelligence (AI) developers to optimize their processes, create smarter software, and develop innovative products.
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So how do you hire AI developers? If you’re looking to hire an AI developer for your team or company but aren’t sure where to begin, our guide is here to help! In this guide we’ll cover everything you need to know about AI; from the job market to the developer skills to look out for so that you can find the best AI candidates for your organization.
What is Artificial Intelligence?
In its most simplest form, Artificial Intelligence (AI) can be defined as the process by which machines replicate human intelligence. By leveraging massive datasets and employing statistical analysis, AI systems can identify patterns, predict future events, and execute tasks with superior efficiency compared to humans.
What are Some Different Types of AI Solutions?
AI can come in many forms depending on the specific task it is required to perform. Below are some examples of different types of AI solutions:
- Machine Learning: This type of AI enables machines to learn from data and improve their performance over time. It involves the use of algorithms and statistical models that identify patterns in data and make predictions or decisions without explicit programming.
- Deep Learning: This is a specific subset of machine learning that relies on artificial neural networks in which multiple layers of processing are used to extract increasingly complex features from data as they progress through the layers. Deep Learning models work by simulating the decision-making process of the human brain, allowing for complex pattern recognition and advanced decision-making capabilities. The multiple layers of interconnected nodes in deep neural networks enable the models to automatically learn hierarchical representations of the data, leading to improved performance in tasks such as image and speech recognition, natural language processing, and other complex problem domains.
- Natural Language Processing (NLP): NLP focuses on enabling machines to understand, interpret, and generate human language. It encompasses tasks such as language translation, sentiment analysis, and speech recognition.
- Computer Vision: A field of AI that allows companies to create applications that derive valuable insights from digital images or video and subsequently take actions or provide recommendations based on those insights.
- Predictive Analytics: Combines data mining, predictive modeling, and machine learning techniques to analyze both present and past data, enabling accurate predictions about future events. These patterns and relationships within the data, empower decision-makers to make informed decisions based on reliable insights.
The State of Hiring AI Developers in 2023
Over the last few years, Artificial Intelligence (AI) and Machine Learning (ML) based technologies have produced significant advancements across various industries ranging from medicine and finance to transportation. Today AI can assist in writing code, diagnosing patients using MRI images, detecting instances of financial fraud, and directing autonomous vehicles.
But the problem for companies is that AI is extremely complicated, and the talent pool of those qualified to perform cutting-edge research and engineering is extremely small. As the field rapidly expands and AI becomes increasingly mainstream, educational institutions are grappling with the task of training the number of AI and ML professionals needed to meet the growing demand.
With the shortage of AI talent predicted to persist over the next decade, many hiring and recruiting teams are finding it challenging to hire AI developers. The scarcity of skilled professionals poses a hurdle for companies aiming to capitalize on the benefits of AI technology.
However, you can maximize your success with the right techniques — starting with a clear understanding of who an AI developer is and the nuances between the different types.
What do Artificial Intelligence (AI) Developers do?
An artificial intelligence (AI) developer applies their expertise in engineering and computer science to create computer systems and applications that can solve problems the way a human would. AI developers integrate AI functionality via algorithms and logic into software applications. Typically, AI developers are primarily strong programmers, first and foremost, with additional expertise in designing networks, tuning parameters, and selecting activation functions.
The primary role of an AI engineer is to augment the intelligence and activities of a human by developing AI computer systems and applications that can work autonomously from humans as much as possible to solve business problems. While AI can be used to automate processes, process large-scale amounts of data, interact with customers, or predict outcomes, it is important to note that humans will always remain indispensable as they are responsible for addressing any issues that the AI solution has not been specifically trained to handle.
You might hire an artificial intelligence engineer to:
- Manage and direct research and development (R&D) activities aligned with the organization’s AI strategy, ensuring they meet the desired objectives.
- Gain an in-depth understanding of the challenges faced by the company and its clients, and explore how AI can contribute to developing effective solutions.
- Collaborate with cross-functional teams to identify opportunities where AI can be applied to enhance existing processes, improve efficiency, or create innovative products or services.
- Design and develop AI models, algorithms, and software applications tailored to address specific business needs and challenges.
Skills and Qualifications to Look for in an AI (Artificial Intelligence) Developer?
Understanding which skills and qualifications are required and which are preferred can help you determine the best-fit candidates. Although every organization has different needs, many recruiters and hiring managers look for artificial intelligence engineers with the following skills and qualifications.
- Two or more years of experience in applying AI techniques to real-world scenarios, showcasing the ability to develop practical and comprehensive solutions.
- Proven experience with ML and deep learning methodologies, including hands-on experience with frameworks such as TensorFlow. This includes a solid understanding of model development, training, and evaluation.
- Proficiency in Python, a widely used language in the AI field, which allows engineers to implement AI algorithms, manipulate data, and build scalable applications efficiently.
- Knowledge of basic algorithms, object-oriented and functional design principles, and best practice patterns. This ensures the development of reliable, maintainable, and scalable AI solutions.
- Experience with REST API development, NoSQL design, RDBMS design and optimizations.
- Familiarity with cloud environments, such as AWS, Azure, or Google Cloud, and experience leveraging cloud services for AI applications. This includes deploying, scaling, and managing AI models in the cloud.
Nearshore AI Development: Discovering What, How and Why to use it.
What is Nearshore AI Development?
Nearshore AI development involves outsourcing your AI development needs to a country closer to your home location, like Costa Rica or Mexico. This form of recruiting can help you to jumpstart your AI-based digital transformation initiatives, by utilizing the expertise, capabilities and experience of seasoned data scientists, data specialists and service design teams.
The main reason why US companies are exploring Nearshore AI development is because it enables greater collaboration, responsiveness, and convenience. When you work with a nearshore provider, as opposed to other outsourcing models, projects can be completed and deployed faster, you can be assured that the solution was designed to fit your exact needs, it meets your quality standards and you save costs.
Why Does it Make Sense to Use a Nearshore Provider for AI Projects?
Building an AI algorithm is a highly specialized and complex process that requires the expertise of a skilled software developer. Most companies do not have that skill set in house, since it’s not a role that is needed on a daily basis. In addition, there continues to be a shortage of AI talent, so even if they wanted to hire internally, they are hard-pressed to do so. Companies find that they’re able to secure the talent they need to initiate an AI project more effectively through a nearshore partner.
In addition, building an AI model requires large amounts of data. Training models requires manually identifying, classifying and tagging the data. Few mid-sized companies have the manpower and time to dedicate to this arduous task. Nearshore providers can therefore provide data specialists who have been rigorously trained to efficiently classify data. Typically, nearshore AI development teams work in secure environments and they are under NDAs to ensure confidentiality.
How to Choose Where to Nearshore your AI Projects?
When selecting a nearshoring location, it’s important to understand the different labor laws and other federal regulations. For example, some countries have labor laws that limit work to 40 hours per week and anything over that is considered overtime. Additionally, Intellectual Property (IP) interests can be substantially different between countries. And, when it comes to highly regulated industries, such as government, healthcare or banking, data privacy laws may prevent the sharing of some information across country borders.
Another thing to consider is the education, certifications and expertise of the team you will be working with. Inquire about this when meeting the team and research the university rankings, engineering programs and graduation rates of the region. A good nearshoring partner will have access to highly relevant and qualified professionals with the technical skills required to develop next-generation AI solutions.
The region you are considering also should have a vibrant entrepreneurial ecosystem, with incentives that reward entrepreneurial pursuits. Look for regions that promote accelerator or incubator programs, offer tax incentives for start-ups, hackathons and tech associations. These types of locations are often home to innovative and inspired tech firms, and graduating students and rising professionals who remain in the region.
How do you Structure an AI Development team?
A successful AI development team will generally incorporate the following elements.
- Data Team: This team is responsible for ingesting, processing and analyzing the data. Typically, you’ll find Data Scientists, Data Engineers and Machine Learning Engineers on the Data Team.
- Algorithm/Research team: This team, consisting of Deep Learning and ML Engineers, drives the development of your AI’s foundation. As companies grow, they may add a Research Team to explore new ways of solving business problems by developing AI, staffed by ML Researchers, Computer Vision Researchers and Natural Language Processing Researchers.
- Infrastructure/Platform Team: These engineers are responsible for building, maintaining, and scaling the computer infrastructure. Backend software engineers, Infrastructure engineers, Platform engineers, MLOps DevOps engineers, Site Reliability Engineers, Security Engineers, and System Engineers are part of the infrastructure team.
- Application Team: This team creates the app or product that your customers interact with. It consists of Frontend and Fullstack engineers, UI/UX designers, and Product Managers.
Why Nearshoring AI Development is Better than Hiring In-House?
When you outsource projects or even specific parts of a project, you eliminate the risk and overhead associated with the costs and permanence of having a full-time employee (FTE). You only pay for what you need, when you need it.
How to Hire a Good AI Nearshoring Company?
You should do your research before hiring a nearshoring partner; determine which model will be the best fit for your company. For example:
- Staff Augmentation: Where you outsource specific components of the software development process to external vendors or freelancers while keeping the core development team in-house. This approach can help leverage external expertise, access specialized skills, reduce costs, and scale resources as needed.
- Fully Outsourced Development: Where the entire software development process is outsourced to the nearshore vendor. The nearshore partner takes responsibility for the entire project, including development, testing, and maintenance. This model allows organizations to focus on their core business functions while benefiting from the expertise and experience of the nearshore partner. It is often chosen when there is a lack of in-house resources or expertise, or when cost-effectiveness is a key consideration.
You should also take a tour of the facilities and ask to meet specifically with the team that will work on your project. A good nearshoring partner will have access to highly relevant and qualified professionals with the technical skills required to develop next-generation AI solutions.
How to Choose the Best AI Nearshore Vendor?
It’s important to do your homework and consider the location. Since it’s a partnership, it’s important that you are in proximity to operate in similar time zones, with the same regulatory and data regulations and cultures. Also, inquire about projects that the outsourcing provider has completed that may be similar to your own, and meet the team that will be working on your project.
Ready to Hire an Artificial Intelligence Developer?
If you are planning to scale your AI engineering team, try Next Idea Tech. We make it easy for companies to hire by offering pre-vetted nearshore AI developers.
Our talent delivery team at Next Idea Tech believes that the best way to find the right candidate is to start with the project and its staffing needs. We recommend that you define what kind of AI skills and expertise you’re looking for and why it’s important for your business in order to narrow down the candidates.