🚀 9 AI Career Tips for Students, Career-Changers, and New Grads
Written by: Michael Hwang, Co-founder and CSO of Datumo
Breaking into the AI field can feel overwhelming. There’s too much hype, too many buzzwords, and no clear roadmap.If you’re a student, a recent graduate, or someone looking to transition into AI from another field, you’re not alone.
When I was starting out, I had a lot of questions and not enough honest answers. So I wrote down 9 straightforward tips I wish someone had told me earlier—no fluff, just things that actually help.
This might sound obvious if you’re already in the AI industry — you’ve probably heard it all before.
A lot of people chose Computer Science simply because AI was “hot.” I was one of them. When I entered university, the iPhone had just launched, mobile was booming, and Computer Science felt like the smartest choice.
But once I started coding… I realized I didn’t enjoy it. That led to a long period of career confusion.
The AI industry is broader than people think. Some of the roles include:
- AI Researcher
- AI Engineer
- Product/Service Developer
- Project Manager
- AI Linguist
- Sales
- Marketing
- Business Development
- Employer Relations
- Safety / Policy / Regulation
- AI-focused Investor
There are many more.
From people who do deep research and coding in solitude, to people-oriented roles like BDs and Sales—this industry has room for every type of person.
Rather than choosing a promising job and living unhappily, it’s more important to find something that fits your personality and aptitude.
For example, I majored in CS, but I realized early on that sitting still and coding all day didn’t suit me. Luckily, I figured that out during my first or second year of university and explored alternatives—which led me to start my first startup company.
Now, I focus on management, fundraising, and customer development as a co-founder at Datumo .
And the people I’ve met in this industry? They don’t just have backgrounds in math, CS, or AI. I’ve met lawyers, PE majors, philosophers (!), seminarian(!!) and many linguists—who are especially important in this field.
It’s great if you find your direction early. But even if not, it’s totally fine. Take your time. Being one or two years behind others is no big deal.
I know a Canadian who taught English in Korea for 10 years. During the pandemic, he went back to Canada, started learning AI, and now he’s a team lead at an AI division in a NYSE-listed company.
He entered the field in his 30s.
In fact, there are tons of people who only got into AI after AlphaGo or ChatGPT.
Me? Even though I studied CS, I didn’t know that AI models need data to learn—until I joined Datumo as a founding member in my 30s.
(That someone like me now gives AI talks still makes me laugh.)
My younger sibling studied music, earned a master’s and PhD from a prestigious university, and is now studying to become a lawyer specializing in AI compliance, regulation, and corporate policy.
If your situation allows, take your time. Better to be “late” and aligned than “early” and full of regret.
GPT is surprisingly smart and helpful when it comes to career advice!
Open chat mode and ask:
- What kinds of jobs exist in AI?
- What does an AI linguist actually do?
- Which roles are promising?
- Which might suit my personality?
It’s not a bad idea to use AI to find your path in AI.
LinkedIn is a great platform to connect across industries.
Especially for career advice, there are so many people willing to spare their time to help you.
So don’t hesitate—reach out, message someone, ask for a coffee chat.
Of course:
- Be polite and respectful
- Do some research about the person and their job
- Ask thoughtful questions
Some people may not respond—or may read your message and ignore it.
That’s okay. The world is full of people. Just message the next one.
You never know—one conversation could lead to a job or a career you’d never thought of.
As I said earlier, I started learning about AI in my 30s.
Not knowing isn’t embarrassing. Realizing you don’t know is actually admirable.
There are so many free resources available. I recommend deeplearning.ai by Andrew Ng
You can choose based on your level and how deep you want to go.
And if your goal isn’t to become a researcher, you don’t need to read papers or code. There are tons of ways to gain a solid general understanding of the AI field.
Afraid of math or coding? That’s fine. Start light. Use podcasts, explainers, GPT—whatever works for you.
One of the best ways to understand AI is to experience it.
Try internships, side projects, open-source contributions, or community collaborations. It doesn’t have to be at a big company.
Even small projects help you:
- Learn how AI is actually applied
- See what fits your strengths
- Build a portfolio
Even if your skills aren’t strong yet, that’s okay. Teams love people who are eager and reliable.
AI is global. Most of the knowledge, research, and communication happens in English.
You don’t need to be fluent. Just be able to read, write, and speak enough to not be afraid of it. And of course, you can get help from AI 🙂
Start small—use newsletters, subtitled videos, explainers.
Think of English as a tool, not a test.
Especially when you’re a student, forget about the job title.
Ask:
- Do I like working with people or solo?
- Do I prefer writing, visuals, or data?
- Do I enjoy long focus or fast feedback?
The answers will help guide you toward your own direction in AI.
The world is big and full of opportunities.
Life is short, but you don’t need to rush.
Meet people. Attend events. Reflect. Study. Try things.
Bit by bit, find what suits you.
And once you do—use it to make the world a little better, in your own way.
I’m rooting for you.
At DATUMO, Inc., we help companies build trustworthy GenAI systems — through evaluation, red-teaming, and curated datasets(especially Korean Language Datasets including books, QA datasets, private benchmarks).
We’re proud to work with global leaders like Samsung, LG, and KB Financial Group.
If your team is building with LLMs and cares about quality, we’d love to talk.
