Table of Contents
Last updated August 23, 2024
The umbrella term, Artificial Intelligence (AI), has existed since the 1950’s, but has accelerated rapidly in the last 10 years. Machine Learning (ML) is a subcomponent of AI that uses specific statistical algorithms to process massive amounts of data in order to produce insights, predictions, and unique outputs.
As Evan Shy, the CEO of Coding Temple, describes: “The World Economic Forum predicts that tech advancements, from automation, artificial intelligence, to robotics, will displace 85 million jobs by 2025. However, this same technology will also create 97 million new jobs in areas like data analysis, software development, and cybersecurity. Ultimately it’ll depend on how you prepare for these inevitable changes.”
Machine learning and AI (Artificial Intelligence) bootcamps last 12 to 24 weeks and cost anywhere from free to $30,000. Realistically, a complete beginner in tech is not going to become an AI Engineer in 12 weeks. If you don't have a technical background, then start with a Software Engineering or Data Science bootcamp. Once you graduate, find an entry-level job working with data, and continue to learn! You can also add to your skill set with an entry-level AI Intro course or an advanced course on AI.
Expect a job description for a Machine Learning Engineer or AI Engineer to ask for knowledge of Python and Spark. You may also see generative AI tools like ChatGPT or OpenAI. Codesmith’s Director of Machine Learning, Weylin Wagnon, says, “You need to be able to work with large amounts of data, be a smart programmer, understand neural networks, and have machine learning skills…in general, machine learning is equal parts math, statistics, computer science, and voodoo.”
Varun Kumar, an AI Engineer who graduated from Flatiron School, says his job is “Part data wrangling, part coding, and part researching new techniques and software that has been developed in dealing with large language models and processing natural language.” Varun breaks it down even further into six categories of on-the-job requirements:
Traditional tech roles like Software Engineers and Data Scientists can incorporate AI and Machine Learning skills into their current jobs. However, companies are now hiring for AI-specific roles like Prompt Engineer and AI Integration Specialist. Expect a lot of variability between job listings until these roles become more defined.
Some common ML/AI job titles include:
To get started in AI, Machine Learning and AI Engineers need a variety of skills and continuous learning is a must. According to Carianne Burnley, a Career Coach at Springboard, “The most widely used programming language in AI is Python, and the libraries and frameworks associated with it. Knowing other languages like Java and C++ can be helpful as well.”
The most important AI technical skills and languages are:
Even if you learn all of these topics at an AI Bootcamp, expect to continue learning “on the job” where you'll be working with data at scale. Imesh Ekanayake, a mentor at Metana bootcamp, stresses, "I find that where people often lack skills is when attempting to handle tasks at scale, especially in the cloud. Dealing with multi-terabyte or terabyte-scale datasets adds a whole new level of complexity to the equation."
Employers are also looking for AI professionals with strong soft skills to help them integrate into the workplace and achieve success. Some soft skills that are important for AI and Machine Learning Engineers are:
Overall, the job market for artificial intelligence positions is expected to grow at a rate that is faster than average over the next ten years, with Machine Learning and AI positions seeing a 53 percent growth rate during that time, making it #8 on Indeed’s Best Jobs of 2023 list.
The average Machine Learning Engineer salary is $161,407 per year, but salary is largely dependent on experience. The average base salary for an entry-level Machine Learning Engineer is $97,205 per year, $162,774 for a mid-level position, and $185,416 for Engineers with more than ten years of experience. Location matters, too, with the average salary around $205,000 for a Machine Learning Engineer in cities such as New York, with similar wages for other large metropolitan areas like San Francisco, Austin, and San Diego.
Newly-created AI roles like Prompt Engineer can earn up to $335,000 per year.
If you have a degree in computer science or a strong technical background, consider an AI/machine learning bootcamp or an advanced AI course. Machine learning & AI bootcamps last between 12-24 weeks and cost anywhere from free to $30,000.
If you don't have a technical background or degree, start with a Software Engineering or Data Science bootcamp. Once you graduate, find an entry-level job working with data, and continue to learn new skills to get into AI.
The great thing about a career in AI and Machine Learning is that there is a wide variety of areas in which you can specialize, largely due to the swift growth of the AI industry. Popular fields for AI careers include healthcare, government, tech, finance, manufacturing, and e-commerce. In addition to Machine Learning Engineer, AI career positions you can consider are:
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Le Wagon is a global tech training provider that offers full-time, in-person and online bootcamps in Web Development, Data Science, and Data Analytics. Le Wagon also offers part-time courses in Web Analytics, Python & Machine Learning, Growth & Data Automation, and Data Analytics Essentials. Le Wagon is aimed at individuals seeking to change careers or acquire specific skills. Le Wagon’s training has helped more than 18,000 students accelerate their careers, transition into tech, or launch startups. Le Wagon was founded in 2013 in Paris, and now has in-person campuses in over 40 cities and 25 countries.
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