How Do I Get a Job in AI? Is a Career in Artificial Intelligence a Good Idea and How Do I Become a Professional?

Artificial intelligence is one of the most in-demand and lucrative tech fields today. But for those looking to break into the industry, key questions arise: How do I get an AI job, especially with no experience? Is pursuing a career in AI a good idea long-term? And how do I ultimately become a professional in this complex space?

In this comprehensive guide, we’ll cover:

  • Vital reasons why AI offers incredible career potential now
  • Most in-demand AI roles and skills companies are hiring for
  • Core education and knowledge you need to gain
  • How to get initial AI experience through hands-on projects
  • Additional tips for entering and advancing in the AI field
  • Examples of AI career paths at leading companies
  • And plenty more guidance to set you on the path to an exciting, high-growth AI career!

Let’s delve into everything you need to launch a successful and meaningful career in artificial intelligence.

Coursera's "AI for Everyone" course featuring Andrew Ng as the instructor, offering an accessible introduction to AI for a wide audience.

Why is Now a Great Time to Pursue a Career in AI?

Artificial intelligence has gone from futuristic fantasy to mainstream reality almost overnight. Several key factors make now an ideal time to enter the AI field:

  • Surging Market Demand – AI adoption is skyrocketing across industries fueling unprecedented hiring demand for AI talent. The market is projected to surpass $500 billion by 2024.
  • Incredible Salaries – AI skills allow professionals to command top salaries sometimes exceeding $500k at leading companies. The pay potential draws many to the field.
  • Abundant Job Opportunities – AI job postings have seen a whopping 74% annual growth highlighting huge open roles needing skilled talent. Openings span technical and non-technical positions.
  • Rapid Technological Advances – Accelerating AI breakthroughs in areas like machine learning and neural networks underlie the growing career possibilities. It’s a uniquely exciting time in AI history.
  • Positive Societal Impact – AI unlocks incredible opportunities to use technology for social good – improving lives, health, the environment and more. Work with meaning attracts talent.

The surging demand for AI expertise needed to fuel innovative new applications makes it a ripe field for aspiring professionals to enter now.

Most In-Demand AI Jobs and Required Skills

Many roles exist within the AI ecosystem for professionals with varying backgrounds to thrive in. Here are some current in-demand AI careers and associated required skills:

AI Engineers – Develop AI systems end-to-end. Skills needed: Python, TensorFlow, PyTorch, mathematics, statistics, MLops, cloud platforms.

Data Scientists – Leverage data to build ML models. Skills: Python, SQL, statistics, ML theory and algorithms, business acumen, data visualization.

Machine Learning Engineers – Specialize in optimizing ML model performance. Skills: Python, PyTorch, TensorFlow, model deployment, distributed systems, AWS/Azure.

AI Business Analysts – Bridge technical and business needs. Skills: AI strategy, project management, communication, technology basics.

AI Product Managers – Strategize AI product development and application. Skills: Technical understanding, product strategy, research, project management.

AI Research Scientists – Advance leading edge research and models. Skills: PhD in CS/math, research, Python, ML theory, publications.

AI Ethicists – Ensure ethical, responsible AI development. Skills: Technical basics, philosophy, policy analysis, risk assessment.

AI Sales Professionals – Sell AI products, services and solutions. Skills: Understanding AI value propositions and applications, sales skills.

This sampling highlights the diversity of AI roles needing both deep technical talent as well as creative, strategic thinkers to support practical applications.

What Foundational Education is Needed to Enter AI?

While some AI careers like ethicists or sales professionals permit alternative backgrounds, most technical roles do require the following core education:

  • Bachelor’s degree in computer science, data science, math, statistics, electrical engineering or related quantitative field – Provides fundamental programming abilities and exposure to algorithms, data structures, analysis techniques and ML foundations.
  • Master’s degree in AI, machine learning, data science, CS or related field – Allows focus on AI coursework and research projects. Especially useful for specializing in AI engineering or research but not always required.
  • PhD for select research roles – A PhD involving published AI research and innovations is mandatory for the most advanced research scientist roles pushing forward new techniques.

However, those passionate about entering the field should not be deterred if lacking formal credentials. Continuing education programs and hands-on learning can still break into AI!

asian ai engineer student uses her laptop as an ai robot watches

How to Gain Initial AI Experience Through Projects

Hands-on AI projects allow beginners to start skill building before or alongside education. Self-study tactics include:

  • Take online AI courses on platforms like Coursera, Udacity, Udemy, and EdX covering topics like Python programming, machine learning fundamentals, TensorFlow, AI applications and more.
  • Join AI communities online and locally to connect with mentors, collaborate on projects, and continuously learn. Great for networking too.
  • Create AI side projects like building a machine learning web app, testing models, analyzing open datasets on Kaggle or contributing to open source AI tools on GitHub.
  • Do AI internships either through university programs or directly applying. Exposure to real-world applications is invaluable experience.
  • Consider an AI coding bootcamp like Springboard to condense learning. These intensive multi-month programs equip you with in-demand skills through hands-on curriculum and career support.

Gaining recognized AI credentials coupled with project experience is a powerful combination when seeking that first role. Never stop learning!

Smiling Indian student standing confidently alongside AI robotics, showcasing expertise in AI Ethics Engineering.

Additional Tips for Starting and Advancing in an AI Career

Beyond foundational education and skills, focus on:

  • Building a robust professional portfolio to showcase AI projects and impact to employers.
  • Mastering AI tools and frameworks like Python data science libraries (NumPy, Pandas, Matplotlib), TensorFlow, PyTorch. Ensure you can apply them.
  • Understanding the full machine learning lifecycle – from data preprocessing to model optimization, evaluation, and deployment.
  • Demonstrating business value by articulating AI use cases, results and insights – not just technical details.
  • Developing soft skills like communication, collaboration, curiosity and ethics. AI teams need diversity.
  • Specializing in the countless AI application domains like computer vision, NLP, recommendations, predictions etc.
  • Striving for excellence by continuously learning, improving systems, and keeping pace with innovation. AI advances daily!

The advice in this guide combined with passion and perseverance prepares you to take advantage of the incredible AI career opportunities ahead.

For more details on AI career progression steps, see these additional guides:

Exciting possibilities await those eager to take the plunge into artificial intelligence as a career. With dedication and guided preparation, your dream AI role is within reach. Let’s connect if you need any guidance getting started!

Frequently Asked AI Career Questions

See answers to some additional popular AI career questions below:

How much do AI professionals earn? Salaries for AI careers range widely by role and experience level but tend to be very lucrative, sometimes exceeding $500k at top companies. The national average sits around $150k currently.

Do I need to be extremely technical for AI jobs? Some degree of technical proficiency is required for hands-on roles like engineers. But many AI jobs like project or product management require only general tech understanding along with other soft skills. Look for roles aligning to your strengths.

Is AI a dying field? On the contrary, AI adoption is still in the very early stages. With projected growth to surpass $500 billion by 2024 and increasing integration across industries, AI will continue rapidly expanding for decades to come. Job demand is only increasing.

How long does it take to switch careers to AI? The timeline depends heavily on your starting baseline. Those with more transferable skills may transition faster than needing to start from scratch. Consistently dedicating 6-12 months to focused upskilling and project work can position you for entry roles.

What are disadvantages or risks of an AI career? Work-life balance can suffer due to long hours needed to be successful. The rapid pace of innovation also requires continuous learning and skills updating. Ethical pressures around AI development require awareness as well. But overall, AI offers incredible positives for those willing to work hard.

Ready to define your future in artificial intelligence? Let’s connect to start strategizing your AI career game plan!


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