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October 15th, 2025
Top AI Jobs for College Grads
Artificial Intelligence is undoubtedly the most disruptive new technology since the introduction of the internet. It will make an impact in nearly every industry as well as within our everyday lives. In fact, many business productivity applications are aggressively incorporating AI into their products due to its transformative nature. Due to the profound change that AI is introducing into our world, it will significantly impact the job opportunities available to recent college graduates. The impact of AI is already being felt by recent grads. According to TechCrunch, AI has caused Big Tech companies to reduce hiring of new graduates by 25% from 2023 to 2024. Also, entry level jobs that were traditionally filled by new graduates are increasingly becoming automated by AI. To make matters even more challenging, colleges typically lag in adding emerging technologies to their curriculum. Therefore, many young people are entering the workforce with little to no real-world experience with AI. Because of these issues, nearly all college graduates are at risk of encountering limited job opportunities due to the impact of Artificial Intelligence.
It is not all doom and gloom for recent grads though. There are many new AI jobs being created by companies working in the Artificial Intelligence industry. Smart graduates will recognize the value of having first-hand experience with AI, as well as knowledge of the AI jobs that are available for workers.
AI jobs for new college grads
AI Research Assistant
Other titles: Research Assistant (AI/ML); Junior Research Engineer
Average US Starting Salary: $47,885/year
What they do
AI research assistants perform a lot of manual work while assisting AI software engineers or AI data scientists in completing their projects. The role consists of manual data collection, feeding data into a machine learning algorithm, and optimizing an AI search engine.
Why it is in demand
Organizations that are embarking upon AI projects need people to collect the data to be input into their machine learning models.
Required skills
Proficiency in Python programming, experience and knowledge of machine learning frameworks, mathematical and statistical skills. Critical thinking, problem-solving, and communication skills. Research paper analysis and scientific writing skills.
AI Prompt Engineer
Other titles: AI Content Engineer, generative AI specialist
Average US Starting Salary: $92,792/year
What they do
Large Language Models (LLM) serve as the core component of AI tools like ChatGPT and Apple’s Siri (NASDAQ: AAPL). LLM’s allow these types of applications to communicate with users using natural language via text and speech. All LLM AI applications require prompts in order to generate output. The quality of the output of the AI tool is often dependent on the quality of the input (prompts). A prompt engineer develops specific prompts for AI models to ensure that they generate both high quality and accurate results. These prompts include specific phrases, words and symbols designed to generate the highest quality output.
Why it is in demand
As more users adopt LLM AI applications, the variety of user prompts input into the AI applications increase dramatically. With so many non-standardized and often poorly structured prompts used, AI models are prone to generating lower quality or irrelevant results. The Prompt Engineer improves the quality of the AI output by designing prompt templates. They make AI more useful to users, and the quality of the output more accurate, which helps to increase overall AI adoption.
Required skills
AI Prompt Engineers require a mix of technical and non-technical skills. This includes extensive knowledge of Natural Language Processing (NLP), Python for writing prompts, understanding the fundamentals of machine learning, the ability to analyze AI data output, experience with API’s, familiarity with AI tools such as ChatGPT, strong writing skills, creative and critical thinking skills, problem solving skills, adaptability, and a willingness to continuously learn.
Entry-level Machine Learning Engineer
Other titles: Junior Machine Learning Engineer, Associate Machine Learning Engineer, AI/ML Software Engineer, AI Engineer, and Junior Data Scientist
Average US starting salary: $112,000/year
What they do
Machine Learning Engineers build, train, and deploy machine learning models for predictions, personalization, and automation under the guidance of senior engineers.
Why it is in demand
Machine Learning is a core component to nearly every AI-driven product. As companies expand their AI features, they require a large number of machine learning engineers to develop their products.
Required skills
Experience with Python development. Strong math skills, particularly with calculus, linear algebra, and probability analysis to design algorithms. Experience with Machine Learning algorithms and frameworks. Experience with data cleansing, data handling, preprocessing, feature engineering, and data modeling. Experience with deploying in cloud environments such as Azure and AWS. An understanding of the software development processes, including version control, debugging, and deployment. Problem solving skills, communication skills, collaboration skills, and the ability to adapt and continuously learn.
AI data analyst
Other titles: Data Scientist I, Business Intelligence Analyst, Machine Learning Analyst
Average US starting salary: $65,491/year
What they do
An AI data analyst uses AI and machine learning (ML) to analyze large data sets, identify trends, build predictive models, and build automated processes.
Required skills
Data analytics, business knowledge, the ability to communicate with stakeholders, the ability to present data clearly and efficiently. Helping decision makers understand data output to improve decisions. Technical skills include experience with SQL, Python, pandas, visualization tools, and basic ML algorithms.
AI Data Scientist
Other titles: Data architect, Computer Vision Engineer
Average US Starting Salary: $165,018/year
What they do
AI data scientists develop, implement, and evaluate AI models and algorithms to extract insights from data. They generally use machine learning to develop AI models.
Why it is in demand
Organizations need AI Data Scientists to create AI models, interpret the data, and help guide the organization’s strategic AI investments.
Required skills
A rich programming background (especially python/R), statistics, machine learning, database knowledge, and data cleansing & visualization. An AI data scientist must also have strong problem solving skills and the ability to explain complex information to non-technical audiences.
AI Software Engineer
Other titles: AI App Developer, Software Engineer (AI/ML), Full Stack Engineer (AI)
Average US Starting Salary: $166,000/year
What they do
An AI software engineer designs, develops, and deploys AI models. Some projects may be proprietary full-stack AI applications, others may be through integrations with 3rd party AI platforms such as ChatGPT, Google Gemini, as well as others. The types of products they build would include chatbots, recommendation systems, or automation tools.
Why it is in demand
AI is transforming industries rapidly and AI software engineers are required to build, integrate, and maintain complex artificial intelligence systems.
Required skills
Programming languages such as Python, Java, or C++ to write, debug, and optimize code. Familiarity with libraries such as TensorFlow and PyTorch. A deep understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), neural networks and deep learning architectures. Foundation in linear algebra and calculus to develop and validate AI models. Basic computer science knowledge. Experience integrating into systems with API’s; prompt engineering; and experience with Node.js or React. Good communication skills.
ML Data Engineer
Other titles: Data Engineer I, MLOps Associate, ML Ops Engineer, Cloud ML Engineer
Average US Starting Salary: $129,716/year
What they do
A Machine Learning Data Engineer builds and maintains the data pipelines required to support machine learning models. They also design and manage the IT infrastructure that the AI applications are hosted on. They prepare and optimize the data for training AI models, cleanse data for model input, create scalable AI models, retrain, upgrade, and maintain AI models. The ML data engineer would work closely with AI data scientists, machine learning engineers, and software engineers to ensure that the models are deployed successfully.
Why it is in demand
ML data engineers are required to build and maintain the scalable AI IT infrastructure that all AI systems require. They also play a key role in preparing data for creating AI models.
Required skills
Knowledge of programming languages such as Python, experience with SQL, and non-relational databases such as NoSQL. Experience with big data technologies such as Spark and Hadoop. Experience with server management in cloud platforms such as AWS, MS Azure, and Google Cloud. Experience with data warehousing and data modeling. Strong problem solving and communication skills.
AI Product Manager
Other titles: AI Analyst, Associate AI Product Manager, AI Strategy Analyst
Average US Starting Salary: $159,405/year
What they do
AI product managers are responsible for spearheading and managing AI initiatives. They establish the vision, product roadmap, and entire development lifecycle of AI products. They often work between departments to develop the specifications for the AI projects to provide the best value to the various stakeholders. AI Product Managers also evaluate all of the alternatives for AI technologies, integrations, and hosting platforms and select the best options for the organization’s needs. While crafting the specifications for the AI project, they focus on providing the best user experience to ensure that the AI solution is adopted widely by its users. Upon completion of the AI project, they establish key performance indicators (KPI’s) to measure user adoption and constantly monitor the AI application’s performance against the KPI’s.
Why it is in demand
AI product managers are the true champions of AI initiatives within organizations. Without them, most AI initiatives would fail to gain traction. They devise the AI product strategy and serve as the liaison between the engineering and business teams within the organization. They identify the market opportunities for AI projects and establish the objectives for the AI project’s results. Once AI products are implemented, they are responsible for ensuring that they are continuously enhanced and are meeting the needs of the users.
Required skills
A thorough understanding of AI / Machine learning concepts, experience with the product development lifecycle, the ability to communicate effectively with both highly technical engineers and less technical business team members. Understanding of how data is collected and used in AI models; understanding of the role of AI ethics and data governance; and familiarity with the tools and technologies used to develop AI products. Project management skills, strategic analysis skills, user experience skills, and market research skills are also required.
NLP / LLM Developer
Other titles: Natural Language Processing (NLP) developer, Junior NLP Engineer, LLM Application Developer.
Average US Starting Salary: $104,344/year
What they do
Large Language Models (LLM) are massive language databases that interact with AI applications, which allow them to have a virtual conversation with users. LLM Developers architect sophisticated and scalable AI applications that interact with natural language efficiently. They are responsible for designing the LLM pipeline and integrating it with LLM’s such as ChatGPT, Claude and others.
Why it is in demand
A LLM developer is required for any AI application that users interact with by using natural language. The most popular AI applications use natural language as the user interface.
Required skills
Programming skills, particularly with Python; experience with AI frameworks; experience with vector databases; AI model knowledge, especially with methods to reduce hallucinations; knowledge of the various AI hosting options; knowledge of tools used to scale and monitor AI applications.
Practical steps that recent grads should take to gain AI experience
Build your skills
Learn programming languages such as Python, ML frameworks, and database technologies such as MySQL and NoSQL. Build strong mathematical skills, particularly in statistics, calculus, linear algebra, and probability analysis. Understand AI basics such as prompts, model evaluation, etc. Earn AI certifications by completing courses offered by companies such as Microsoft (NASDAQ: MSFT) and AWS (NASDAQ: AMZN).
Build a portfolio of personal projects
Create personal projects demonstrating your ability to manage data cleansing, model training, language fine tuning, and conducting error analysis. Post the project on GitHub or your personal blog with an explanation of how you completed the projects, how you overcame challenges, and what you learned in the process.
Target entry level AI jobs
Try to get a job in entry level roles such as an AI prompt trainer, a data annotator, a junior ML engineer, an AI compliance assistant, a junior LLM engineer, etc. Gain exposure to more senior level AI engineers who could assist you in your career advancement within the organization.
Get real-world work experience
Get an internship, volunteer or work part time at an organization that is working on AI projects. If possible, freelance on a platform like Upwork for AI projects. Contribute to open source AI projects or work at a startup.
Get exposure to the wider AI community
Participate in AI developer forums, join local AI developer communities, compete in AI hack-a-thons, join AI groups on LinkedIn and other social media platforms, and attend AI meetups. Many of these groups often announce open AI jobs at their meetings.
Be strategic
Design your resume and portfolio in a manner that demonstrates skills which are relevant to job postings. Include keywords, projects, and tools used. Join job boards that specifically list open AI jobs.
Continuously Learn
AI is always changing and will continue to change more rapidly than most technologies. Learn new coding languages, tools, API’s, and best practices to stay on the leading edge of the technology. Learn about AI ethics and governance because they will undoubtedly play a bigger role in AI as the technology matures.
Hot Industries with AI Jobs for Recent Grads
Recent grads should look for opportunities at:
– Tech startups: Software as a Service (SaaS) companies, and generative AI tool providers.
– Healthcare: diagnostics, patient analytics, drug discovery
– Finance / FinTech: Trading algorithms, fraud detection, chatbots
– Manufacturing / Logistics: Predictive maintenance, fleet telematics, fleet dash cameras, route optimization
– Marketing & Advertising: Consumer behavior modeling, content automation
– Political Organizations: Voter behavior modeling, micro-targeting outreach
Rather than becoming a victim to the disruption caused by Artificial Intelligence, graduates can strategically work toward attaining AI jobs that would play key roles in this exciting new industry.
