Advice from Megagon Labs for students ready to go beyond a resume line item and prepare for future AI jobs.
1. Research the company before day one.
Thoroughly research the company’s AI focus areas, ongoing research projects, and key project leaders who may become your supervisor. Read their papers, explore their research directions, and come in with an informed perspective. You can even give yourself a head start by asking mentors for research papers related to your project topic. Knowing the landscape before you arrive signals seriousness and helps you hit the ground running.
2. Be ready to adapt to the needs of the internship.
Research is unpredictable, so the ability to adapt when things don’t go as planned or mentor plans change is essential. Although planning for necessary pivots is your mentor’s responsibility, it can help to show initiative and collaborate on backup strategies. Yoo Yeon Sung, Megagon Labs PhD Intern during Summer 2024, says, “While you’re working on formulating your research project with your mentor, it’s good to have a plan B or plan C, since things don’t always go as planned.”
3. Be proactive about learning beyond your assigned project.
Take the initiative to understand the entire AI development process, from data collection and model training to deployment. Don’t hesitate to ask questions that delve deeper into the “why” behind decisions and technical choices. To help you stand out beyond your project, show genuine interest by exploring opportunities; ask other team members about their work, or attend internal industry talks when available.
4. Build relationships intentionally.
Network with mentors and colleagues within the company. Take advantage of lunch outings, happy hours, and company events, and use the time to have meaningful conversations with fellow interns and company employees. Most importantly, don’t be afraid to show interest and ask about full-time opportunities, recommendations, and referrals. The connections you make here can shape your career long after the internship ends.
5. Communicate clearly and consistently with your mentor.
Yihao Hu, a Summer 2024 Megagon Labs intern, says he believes in the power of clear, effective communication between an intern and their mentor. “It’s very difficult to finish everything assigned in the internship, but most things should be done. Be prepared for a very fast-paced and intense internship.” Regular check-ins, honest progress updates, and active feedback-seeking go a long way. And if you ever feel stuck, having a conversation and asking for support can help you move forward and build your mentor-mentee relationship. Your mentors and the office team are here to support you, and these conversations can help them see your strengths even in moments of difficulty.
6. Document everything as you go.
Actively document key learnings and insights gained throughout the internship. These notes will help you commit the information to memory and can be a great resource for future reference. You’ll thank yourself at the end of the term when it’s time to present your work.
7. Think about how to leverage this experience long-term.
If this is a master’s or PhD research internship, ask yourself, can you incorporate internship findings into your thesis? Or perhaps the internship experience has sparked new research questions or areas of exploration.
When it comes time to choose your PhD committee members, your mentor can serve on your committee, offering complementary expertise. To leverage them in this position, having built a strong mentoring relationship during and after your internship is important.
Don’t let the value stop when the internship does. Stay connected with colleagues, request recommendation letters, and explore how your new skills and network can open doors in research, industry, or both.
Want to learn more tips? Read our AI Internship Guide for Students.
Interested in driving future AI advancements? Megagon Labs invites graduate students to apply for AI research internship positions in Compound AI, NLP, LLMs, machine learning, and human-centered AI. The experience can also help students build the research foundation, mentorship relationships, and practical skills that support a future job in AI.
Written by Megagon Labs
