How to Become an AI Engineer

Artificial Intelligence (AI) has become an integral part of our daily lives, driving innovation across every industry. From personalized shopping experiences to autonomous vehicles, this technology has transformed the way of interaction between businesses and users. Behind the AI are the people who design, develop, train, and deploy AI models and algorithms that improve efficiency.

That’s why AI and Machine Learning roles are in high demand and command impressive salaries. According to Glassdoor, the average expert in the U.S. earns $156,000 annually, with top-tier companies like Google offering even more. So, becoming an AI engineer seems a fulfilling journey that offers numerous professional opportunities.

However, this needs following the right educational pathways, gaining essential AI skills and practical experience. At the same time, companies looking for skilled AI specialists should know what areas to focus on – to make a fully informed decision when hiring. This guide is both for those who want to start a career in AI and projects that need to extend their team with skilled professionals.

Who is an AI Engineer?

AI engineers work with designing, building, and implementing AI models, algorithms, and solutions. They often deal with machine learning (ML), natural language processing (NLP), computer vision, robotics, and other subfields of AI. They also collaborate with data scientists, software developers, and business stakeholders to integrate AI solutions into real-world applications. They use programming languages like Python, R, and Java, along with frameworks like TensorFlow, PyTorch, and Scikit-learn, to create systems capable of learning and adapting to new data.

In a nutshell, AI engineer typically plays a key role in making data-driven decisions, automating processes, and enhancing user experiences. Whether it’s creating a chatbot, improving medical diagnoses with AI tools, or offering personalized shopping experiences, their work has a fundamental impact across different AI related industries.

Why Choose a Career in AI?

An AI engineer career offers numerous benefits, such as progressively growing demand and high salaries. Additionally, developing and implementing AI offers great opportunities to take part in innovative projects and potential for career growth.

Essential Skills and Competencies

What it takes to become an AI specialist? This is a multidisciplinary field. It requires a mix of technical expertise, problem-solving abilities, and a deep understanding of AI in terms of machine learning and data science. Below is a brief summary of key skills needed:

Educational Pathways to Becoming an AI Engineer

There’s no single path to becoming an AI engineer. However, a strong knowledge of computer science, mathematics, and data science will be indispensable. Here’s an overview of the typical educational requirements:

Bachelor’s Degree. A degree in Computer Science, Software Engineering, Data Science, Mathematics, or a related field of AI engineering. Courses in algorithms, programming skills, and data structures are critical.

Master’s Degree. A master’s degree in AI, Machine Learning, or Data Science can boost career prospects and provide in-depth knowledge (while not always required).

Practical Experience. Hands-on experience through internships, projects, or bootcamps. Online platforms like Coursera, edX, and Udemy offer specialized online courses in AI and ML.

Programming Courses

The AI industry keeps evolving rapidly, so continuous learning through certifications, conferences, and research is crucial too. With continuous development in the field, developers should focus on:

• Staying updated on AI frameworks. Following new updates in TensorFlow, PyTorch, and cloud-based AI services.
• Expanding crossfunctional skills. Combining AI expertise with knowledge in business, healthcare, finance, or robotics.
• Contributing to open-source projects. Engaging with the AI community through GitHub, Kaggle, and publications.

University and Online AI Courses

Many prestigious universities and e-learning platforms offer specialized training programs for Artificial Intelligence specialists. Some of the top options are:

• Stanford University’s Machine Learning (Coursera). One of the most popular AI and ML courses for basic concepts.
• MIT Professional Education – AI: Implications for Business Strategy. A deep dive into AI applications for enterprises.
• Harvard University’s CS50’s Introduction to AI with Python. Fundamental AI concepts, including search algorithms, optimization, and deep learning.
• Deep Learning Specialization (Coursera). A focused deep learning course covering neural networks, CNNs, RNNs.

Certifications and Specialized Training for AI Engineers

Steps to becoming an AI expert include certifications and specialized training. They play a key role in confirming the expertise. They are also important for validating their skills and polishing them over time. Whether you’re starting in AI or looking to hire the right expert for your project, relevant certifications and completing specialized courses can set an expert apart in a competitive market. Below are some of the most recognized certifications and training programs for AI engineers:

Industry-Recognized AI Certifications

Earning an industry-recognized certification can confirm proficiency in AI technologies, AI and machine learning models, and deep learning technologies. Some top AI certifications include:

• TensorFlow Developer Certificate (by Google). Focuses on deep learning and neural networks using TensorFlow.
• Microsoft Certified: Azure AI Engineer Associate. Covers Azure AI services ML, and AI solutions in the cloud.
• IBM AI Engineering Professional Certificate. Provides a strong foundation in ML, DL, and AI-powered applications.
• AWS Certified Machine Learning – Specialty. Focuses on AI and ML implementation using AWS cloud services.
• Google Cloud Professional ML Engineer. Covers ML model training, deployment, and optimization in Google Cloud.

Specialized AI Bootcamps

Bootcamps offer hands-on experience to get started in AI engineering. They can provide real-world projects, making them ideal for those who want to enter the AI field quickly. Some reputable AI bootcamps include:

• Springboard AI & Machine Learning Bootcamp. Offers personalized mentorship and real-world projects.
• Udacity AI Engineer Nanodegree. Provides an in-depth AI learning path with NLP, deep learning, and reinforcement learning.
• Data Science Dojo AI & Data Science Bootcamp. Focuses on practical AI applications, Python programming, and ML model development.

Advanced AI Research and Training Programs

To specialize further in research and development, AI engineers need to join advanced training programs:

• OpenAI Scholars Program. Focuses on AI research, reinforcement learning, and ethical AI.
• Fast.ai Deep Learning Course. Offers hands-on deep learning training using PyTorch.Google’s AI Residency Program. A competitive AI research initiative for aspiring AI enthusiasts.

Growing Demand for Artificial Intelligence Engineers and Supply Shortage

The demand for AI engineers is progressively growing. The competition for top AI talent is fierce, with major tech companies offering high salaries and attractive benefits to secure the best ones. That’s why businesses face increasing challenges in finding skilled professionals who can develop, implement, and maintain AI-driven solutions.

Additionally, the rapid evolution of AI technology means that AI engineers are required to become continuously upskilled to stay relevant. This makes it even harder – for both parties – to find a good match and start working together.

Another critical problem is the geographic disparity. Many regions lack a strong AI talent pool, forcing companies to look internationally – that’s why many AI engineers cannot be hired locally. Additionally, hiring in-house often comes with high operational costs. This makes it difficult for startups and mid-sized businesses to afford this option.

At Mobilunity, we specialize in connecting businesses with top-tier AI engineers through a flexible and cost-effective approach. Our dedicated team or FLEX part-time model can give a perfect match. Using our own global talent pool, we can ensure that companies can access the best professionals with the right technical skills and soft skills.

Future Trends and Outlook for Career in AI Engineering

The demand for skilled AI engineers is expected to grow exponentially. From improvements in deep learning to the rise of ethical AI – understanding future trends can help AI engineers and businesses stay ahead of the competition.

Growing Demand for AI Talent

These experts are going to remain in high demand across different AI related industries, including healthcare, finance, automotive, cybersecurity, and e-commerce. Companies are actively investing in AI to enhance automation, improve decision-making, and optimize processes. That’s why AI-driven businesses are expected to generate trillions of dollars in economic value over the next decade.

Key Emerging AI Trends

The field of AI is keeps evolving, with new technologies like:

• Generative AI. AI models are improving the speed and quality of programming and creative industries.
• Edge and IoT AI. The integration of AI enables real-time processing & automation in smart devices, vehicles, and manufacturing.
• Explainable AI (XAI). There is an increasing focus on making AI systems transparent for regulatory compliance.
• Cybersecurity. AI-driven threat detection and prevention tools are becoming essential for protecting digital assets.
• Sustainability. AI is already playing an important role in optimizing energy consumption and reducing carbon footprints.

Career and Average Salary of an AI Engineer

The AI job market is expected to keep growing at a rapid pace. And AI engineers must remain among the top-paying tech professionals.

High salaries. Salary for an AI engineer ranges from $120,000 and $200,000 annually in the U.S., with even higher salaries for specialized roles (Glassdoor).

Diverse career paths. AI professionals can work as machine learning engineers, AI researchers, data scientists, NLP engineers, or AI product managers.

Global opportunities. AI knowledge and skills are in demand worldwide, with leading AI hubs in the U.S., Canada, Europe, and Asia.

Conclusion

The decision to become an Artificial Intelligence engineer can be an exciting and rewarding journey. AI career offers vast opportunities in a rapidly evolving technological landscape. With AI revolutionizing industries such as healthcare, finance, cybersecurity, and autonomous systems – skilled AI engineers are in high demand worldwide.

To succeed as an AI engineer, you must develop a strong foundation in mathematics, programming, and machine learning. This should be accompanied by hands-on experience with real-world AI applications. Getting relevant certifications and networking within the AI community will also boost their value.If you’re passionate about Artificial Intelligence and problem-solving, now is the perfect time to get started. And if you’re looking to hire AI developers with necessary skills and knowledge – let us know about your needs!

Written by:

Bohdan Govdya

Market Researcher