About the role
ASC runs a research lab so our client work stays ahead of the field instead of chasing it. As an Applied Research Engineer you split your time between the two: you investigate new methods (new model architectures, agentic patterns, evaluation techniques) and you turn the ones that prove out into capabilities the delivery teams can use.
This is applied research, judged by whether it ships, not by paper count. You will read the literature, run experiments that answer a real question, and write up findings clearly enough that an engineer can build on them. The best work here ends up in a client system.
What you'll do
- Prototype and evaluate new AI methods against problems ASC actually faces.
- Run rigorous experiments with clear baselines, honest evaluation, and reproducible results.
- Translate promising research into robust, documented capabilities for delivery teams.
- Track the field and brief the wider team on what is worth adopting and what is hype.
- Contribute to the lab’s internal tooling, benchmarks, and shared knowledge.
What we're looking for
- Strong ML fundamentals, typically an advanced degree or equivalent hands-on research experience.
- The ability to read a paper and reproduce or extend it in working code.
- Excellent Python and modern deep-learning frameworks (PyTorch preferred).
- Experimental rigor: you distrust a result until the evaluation is sound.
- Clear technical writing that an engineer can act on.
Nice to have
- Publications, open-source contributions, or competition results.
- Depth in LLMs, agentic systems, retrieval, or multi-modal models.
- Working proficiency in Korean or Japanese.
How we hire
- 1
Intro call
A short conversation about your background, what you want to work on, and how ASC works.
- 2
Technical conversation
A working session on real problems in your area, closer to how we actually work than to a quiz.
- 3
Team and offer
Meet the people you would work with, then a decision, usually within a week.