Introduction

AI may have been around since 1956, but it’s only in recent years that it has gained massive popularity. As more and more industries are finding ways to incorporate the technology into their products or services, new career opportunities arise. To be frank, AI is a great field to work at - it feeds one’s curiosity and it promises a long, secure career ahead. But how to start a job with AI when you have no experience whatsoever? 

Fear not, dear reader, as we’re about to embark on a journey through AI jobs that require little to no experience. Turns out you don’t need a PhD to break into the field. Here’s why.

‍

‍What are AI jobs

We’ve talked more about the essence of AI jobs here, but it doesn’t hurt to say it again - there’s a variety of jobs in the AI field, ranging from creating algorithms and machine learning models that power AI systems to designing and developing robots and intelligent machines that use AI to perform tasks autonomously. Designing, developing and deploying artificial intelligence is all about understanding data, building machine learning models, training neural networks and applying AI to solve real world problems. And that’s where the beauty of AI jobs lies -  their diversity.

When it comes to entry-level AI jobs in particular, they might focus on data preprocessing, model evaluation or assisting more senior engineers with research and development. As you learn and grow, you could work on creating algorithms that power chatbots, recommenders, computer vision applications or even autonomous vehicles.

‍AI applications in different professional fields

If you’re already engaged in one of these fields, the transition to AI may be a way smoother than one might think. Learning how to work on new technologies can open doors and career opportunities not possible before.

• Healthcare
  AI helps in diagnosing diseases, predicting patient outcomes and outlining personalized treatments.
• Finance
  Banks use AI for fraud detection, risk management and automated trading.
• Automotive
  The future is indeed now - AI powers self-driving cars, driver-assist systems and predictive maintenance.
• Education
  AI can be used to personalize educational content based on every student’s individual needs and automate administrative tasks, allowing teachers to focus on what matters most.
• Marketing
  AI is great for analyzing customer data for targeted advertising and personalized content. And don’t even get us started on brainstorming content ideas or optimizing content for SEO purposes.
• Retail
  From inventory management to chatbot customer support, AI streamlines operations.
• Human resources
  AI recruitment is not a new concept and has been at the core of what nPloy does. Utilizing an AI-powered algorithm, nPloy directly connects candidates and employers in a manner similar to dating apps, matching them based on salary expectations, skills, experience, location, and job type.

The list may go on and on - think about it next time you ask Siri if it will rain later in the day.

If you’re thinking about a career in AI, you’ll be even luckier if you’re already working in one of the roles below, as they’re a great stepping stone when it comes to switching fields.

• Data analyst
  Many AI skills overlap here, especially in data handling and visualization. 
• Software engineer
  Software development experience is highly valuable for ML engineering roles.
• Business intelligence
  Experience with data-driven decision-making can ease transition to AI.

Freelance gigs on AI related tasks are another great way to break into the AI industry, so don’t exclude them as an option.

‍

Skills you need to work in AI

You may not yet have experience in AI jobs, but there are some foundational skills and qualifications will help land you a job faster. Let’s go through the list together.

‍Soft skills

• Problem-solving
  Similar to everyday life situations, AI is all about solving complex problems, so creative and logical thinking is a must.
• Analytical thinking
  You’re about to be working with great volumes of data, so an ability to analyze data and results is critical.
• Communication
  Explaining technical concepts clearly is invaluable, especially when working with cross-functional teams.

Math basics

• Linear algebra
  Turns out what you learned at school will come in handy: understanding vectors, matrices and operations is crucial for algorithms like neural networks.
• Statistics and probability
  These two are key for interpreting data, making predictions, and evaluating models.

Programming languages

• Python
  The most popular language in AI due to its simplicity and powerful libraries.
• R
  This one is useful for statistics-heavy projects, especially in research or academia.
• Basic SQL
  It’s essential for handling and querying data stored in databases.

AI and machine learning

• Supervised vs unsupervised learning
  Knowing when to use labeled or unlabeled data.
• Neural networks
  The building blocks of deep learning and modern AI.
  
  

Before diving into the world of AI jobs, you should try to get familiar with the tools and platforms widely used in the field.

• TensorFlow and PyTorch
  Widely used machine learning frameworks for building models.
• Scikit-learn
  Great for beginners to apply standard ML algorithms easily.
• Jupyter Notebooks
  Interactive coding environments perfect for experimentation.

‍

10 еntry-level AI jobs that require little to no experience

Okay, we’ve talked enough and we know this is the part you’re looking for. Let’s see the list. 

• AI/ML intern
  The position is a great way to get hands-on exposure in a real AI environment. The person in this role assists with data collection, model training, and research under supervision. 
• Data Annotation Specialist
  This person manually tags and labels datasets used to train AI models (images, text, audio). The role is important for supervised learning projects.
• Junior Data Analyst
  This role is all about analyzing and visualizing data to help teams understand trends and patterns. It builds foundational skills in data handling and statistics.
• AI Research Assistant
  This person supports AI researchers by running experiments, cleaning data and documenting results. 
• Machine Learning Support Engineer (Associate Level)
  This person helps maintain ML pipelines and assists senior engineers with troubleshooting. It’s basically an entry-level technical support with an AI focus.
• AI Quality Assurance (QA) Tester
  This person tests AI applications and models for accuracy and performance. The role requires attention to detail and basic understanding of AI outputs.
• Junior Natural Language Processing (NLP) Analyst
  This person works on text-based AI projects like chatbots or sentiment analysis with supervision. The role often involves data cleaning and simple modeling tasks.
• AI Content Curator
  The person in this role is responsible for collecting and organizing datasets, documents or training materials for AI projects. The role is suitable for candidates with strong organizational skills.
• Junior Computer Vision Technician
  This person assists with labeling images and videos and basic model training for vision projects. The role is a great entry point in the growing computer vision subfield.
• Data Entry Specialist for AI Projects
  The role is all about input or verifying data used to train AI models and it’s a stepping stone to more technical roles.

‍

Where to find entry-level AI jobs

Well, let’s circle back to that AI-powered hiring solution we talked about earlier. nPloy is your best friend when it comes to looking for entry-level AI jobs. It takes a few steps to do so.

• Create a profile on nPloy
  It takes just a few minutes and the process is designed with you in mind.
• Set the filters
  Help nPloy’s AI-powered algorithm source the most suitable jobs for you by entering your preferences about work model, working times, job type, seniority level and desired salary.
• Apply
  Swipe through the suitable jobs and apply for the ones that speak to you. 

Yes, it’s that easy. Why not try and see for yourself? 
‍

In conclusion‍

Breaking into the AI jobs field is far more accessible than one might think and relatively easier when you know where to loo. Don't be afraid to show your eagerness to dive into the AI field and keep your mind open to all the possiblities - the perfect one may be just a swipe away.

‍

‍

‍