Dreaming of landing an exciting role in artificial intelligence but not sure where to start?
This guide covers top in-demand jobs for breaking into the world of AI and machine learning.
So without further hesitation, let’s go. 👇
The Best Skilled Machine Learning and AI Jobs Are:
Machine Learning Eng
Develop and optimize complex algorithms and models across a wide range of AI projects. Advanced coding and data skills are required.
Combine mechanical, electronic, and AI engineering to build intelligent robotics and systems. Expertise in multiple domains is needed.
Design and develop efficient code to implement AI and ML capabilities into software. Programming language proficiency is mandatory.
Uncover insights from mountains of data through statistical modeling and ML techniques. Advanced math and analytics skills are crucial.
Ensure AI systems are fair and transparent and avoid bias. Often works closely with legal teams. Background in ethics and philosophy preferred.
The Best Machine Learning and AI Jobs That Require No Skills to Get Started Are
Craft prompts to coax helpful responses from large language models and other AI tools. Creativity is vital.
AI Test Engineer
Evaluate AI systems to find flaws, gaps, or distorted outputs without specialized skills. Logical thinking is key.
Manually categorize and tag data to create training sets often used for supervised learning.
Remote Sales Engineer
Explain and convince clients how AI can improve their business. Sales experience trumps technical expertise.
AI Crowdsource Work
Complete simple data tasks that contribute to training AI models online. Basic digital literacy is required.
What Are The Best Skilled Machine Learning and AI Jobs?
The best-in-demand machine learning and AI jobs that require skills in 2023 are:
- Machine Learning Engineer
- Mechatronics Engineer
- Software Engineer
- Data Scientist
- AI Ethicists
1. Machine Learning Engineer
Machine learning engineers develop and optimize the algorithms that power AI systems across industries like finance, healthcare, and transportation. They can work on areas of AI ranging from natural language processing to computer vision and anywhere in between.
You’ll be building predictive models and neural networks which requires proficiency in languages like Python and frameworks like TensorFlow.
A background or bachelor’s degree in computer science, engineering, statistics, or related fields is usually required. Many choose to pursue advanced degrees in machine learning or data science.
Testing, deploying, and maintaining complex models in production environments are also key duties. Strong math skills and software engineering abilities are a must for this role.
Machine learning roles are highly sought after and enable the application of a wide-range of existing skillsets in AI, this makes it the best technical AI job in 2023.
2. Mechatronics Engineer
Mechatronics engineers blend mechanics, electronics, and robotics to create smart machines and automated systems.
A bachelor’s degree in mechatronics is often made up of key subjects from both mechanical and electrical engineering – making it a perfect degree for anyone looking to get into robotics.
Mechatronics engineers can expect to program and train mechanical systems powered by machine learning algorithms to handle complex tasks from assembly lines to surgery.
Strong math, computer science, and engineering abilities are required. Hands-on skills in programming languages like Python and systems like ROS are valued.
As robotics and AI continue to converge, mechatronics engineers are going to become valuable assets in the field of AI and machine learning.
3. Software Engineer
A bachelor’s degree in software engineering or computer science provides fundamental training in programming languages, data structures, algorithms, and software design – making it the perfect background for securing a position in AI.
Formal education in computer engineering or a related field is standard. Hands-on software development experience and knowledge of AI frameworks like TensorFlow and sci-kit learn are common.
As AI advances, software engineers architect and implement the code underlying everything from intelligent chatbots to self-driving cars which are critical in the field.
4. Data Scientist
Data scientists utilize artificial intelligence techniques like machine learning and natural language processing to extract insights from large, complex datasets.
Strong statistical modeling, analytics, and programming skills are required to develop and test predictive algorithms.
Formal education in data science, computer science, or a quantitative field is usually required.
Data scientists need a working knowledge of languages like Python and R, as well as AI/ML frameworks like TensorFlow.
5. AI Ethicists
AI ethicists ensure artificial intelligence systems are developed and used responsibly by assessing risks, evaluating biases, and considering moral implications.
A background in philosophy, ethics, law, or public policy is common. Knowledge of AI, its capabilities and limitations, as well as its impacts on society is crucial.
AI ethicists collaborate with technologists and business leaders to implement ethical AI frameworks and governance.
With algorithms increasingly used in sensitive domains like healthcare and criminal justice, skilled AI ethicists help address transparency, fairness and accountability issues. their interdisciplinary expertise in technology ethics helps guide the conscientious advancement of AI.
What Are The Best No-Skill AI Jobs?
The best in-demand jobs in AI and machine learning that require no skills or qualifications are:
- Prompt Engineer
- AI Test Engineer
- Data Labeler
- Remote Sales Engineer
- AI Crowdsource Contributor
1. Prompt Engineer
Prompt engineers are a new type of artificial intelligence job focused on maximizing the potential of generative AI tools that are controlled with a text input from the user.
Prompt engineering is popular with freelancers as rather than the requirement for advanced technical skills, creativity and communication are key to crafting effective prompts that guide the AI to perform as needed.
A prompt engineer collaborates with data scientists, engineers, and product teams to translate requirements into carefully crafted prompts formatted for AI systems.
Most of the front-end AI tools you’ve used would have a prompt running in the background. Examples might be the various language tools available on Jasper, or personalized avatar makers.
As artificial intelligence becomes more commonplace, prompt engineering will become crucial for extracting the most value from AI tools.
Prompt engineering is by far the easiest way to get involved in AI without having any technical skillset, making it the best non-skilled AI role in 2023.
2. AI Test Engineer
AI test engineers evaluate artificial intelligence systems to uncover flaws, biases, and failures without needing specialized technical skills.
Attention to detail and strong analytical thinking are vital for spotting where algorithmic models fall short or where vulnerabilities may exist.
Test engineers devise clever tests that check how AI handles edge cases. Often the objective of the test engineer is to break, confuse, to make the AI model preform in an unexpected way.
With artificial intelligence integrated into more applications, the importance of thorough AI test engineering is growing. This ensures a safe and effective product is released to the market.
For those interested in contributing to AI’s advancement without coding skills, AI test engineering offers a great entry point.
3. Data Labeler
Data labelers create the training data that powers AI systems by manually categorizing and tagging images, text, videos, and other data. This data is often used in supervised machine-learning applications.
Patience, attention to detail, and consistency are critical for accurately labeling datasets. While data labeling doesn’t require specialized education, familiarity with data science concepts and machine learning are beneficial.
As artificial intelligence advances, demand for large volumes of organized data continues growing. Data labelers help address the labeled data bottleneck which can often slow progress.
For those interested in jumpstarting an AI career without technical expertise, data labeling provides promising on-ramps and upskilling opportunities.
4. Remote Sales Engineer
AI sales engineers demystify artificial intelligence for prospective clients without needing technical expertise. The beauty of these roles is that they are often commission-based – which means it’s easy to get started.
Strong communication skills are essential for explaining how AI capabilities like machine learning and data science can impact their business.
Remote sales engineering provides flexibility combined with lucrative commission potential. A good understanding of your product is important alongside the sales abilities you might have.
For those eager to learn about business applications of technologies like AI without coding skills, sales engineering roles bridge the gap through client education and value communication.
5. AI Crowdsource Contributor
AI crowdsourcing platforms allow people to complete simple data tasks like transcription that collectively train algorithms.
No expertise is required beyond basic digital literacy. Common crowdsourcing activities include labeling images, moderating content or recording speech samples. While microtasks are paid on a per-item basis, dedicated contributors can earn reasonable wages.
For those seeking flexible work opportunities while helping advance artificial intelligence, crowdsourcing provides on-ramps. Participants gain AI exposure and contribute to data science projects that are powering innovations. By democratizing access, crowdsourcing enables anyone to actively shape AI progress.
The beautiful thing about AI and machine learning jobs is that there’s something for everyone.
While most of the jobs are still quite technical, there is an emergence of right-brain creative roles like prompt and test engineering and sales.
So whether you’re a seasoned expert in statistical modeling or a beginner eager to learn, there are more opportunities than ever to pursue a career in AI and machine learning.
The future will be defined by those who design, build, test and most of all, embrace these technologies.