Machine Learning & AI

Considering a career in Machine Learning and AI? We’ve got all the information you need to decide if this career is right for you, including job descriptions, tech requirements, bootcamps that teach AI, and a salary outlook.

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.”

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:

• Research: Stay updated with the latest advancements in the field. This could involve reading research papers, attending seminars or webinars, and participating in online forums and communities. This is crucial as the field of AI and machine learning is evolving rapidly.
• Data Preparation: Work on preparing and pre-processing the data for training language models. This involves collecting data, cleaning it, and converting it into a format that can be used for machine learning.
• Model Development and Training: Design and implement machine learning models. This includes choosing the right algorithms, tuning parameters, and training the model on the prepared data. This process often requires running experiments and making iterative improvements based on the results. Many times, I am building on pre-trained models with either fine tuning, or instruction via prompts.
• Model Evaluation: Evaluate the performance of the models using appropriate metrics. This often involves testing the model on a held‑out validation set and analyzing the results.
• Collaboration: Work closely with other teams, such as product development, to integrate the AI models into products or services. This could involve optimizing the model for deployment, working on the user interface, or addressing user feedback.
• Documentation and Presentation: Document the work for future reference and present findings to stakeholders or to the technical team. This might involve writing technical reports, creating presentations, or showing working code.

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:

• Data Scientist
• Prompt Engineer
• Software Engineer
• Product Manager
• AI Ethics Officer
• AI Data Curator
• AI Trainer
• AI Integration Specialist

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 ,…