ML Engineer (development of Reinforcement Learning based models for architectural design tasks)

Space for All, SPACEWALK

Spacewalk is a Proptech company that uses Artificial Intelligence and Big Data technologies to lead Real Estate market innovations. We provide solutions that help everyone attain the bes t value for their land through Artificial Intelligence.
The company was founded in October 2016 and 4years later, Spacewalk accumulated more than 10 milliondollars in investment.
Our main product, Landbook, creates custom architecture designs, optimized for each parcel based on several factors such as land shape, real estate prices, local laws, etc.
The main customers are public institutions such as LH, SH, and businesses like Nong hyup bank, as well as other major corporations.
Spacewalk rallies experts from numerous fields, such as architecture, real estate, finance, machine learning, data science, web services. We are looking for acollaborator who will face interesting challenges and grow together with Spacewalk to better utilize city'sspace through innovative technologies and impactful projects.


Development of architectural design models using Deep Reinforcement Learning
Development of image processing module related to architectural design (Image Segmentation)
Development of real-estate valuation engine
No prior knowledge of architecture / real estate required

Required Skills

Spacewalk's culture match (Transparency, high performance, high standard, team work)
Experience with machine learning framework (Tensorflow, Pytorch, etc...)
Ability to read, understand, and implement deep learning related papers
Ability to learn and adapt quickly
Ability to write technical documents clearly
Ability to communicate easily with co-workers in order to make correct decisions
Ability to work independently, to reach high quality results


Great understanding of Deep Reinforcement Learning
Practical experience or personal projects using deep learning
Master degree or higher in machine learning or related to computer sciences, computer engineering, mathematical sciences, electronic engineering, etc...
Thesis, publications, papers in machine learning journal, or competition results.

Documents to provide

Portfolio (projects description, period, main contributions)

Interview process

First round : Interview (portfolio)
Second round : Interview, Assignment (optional)
final : CTO Interview
The process might change depending on each situation (for example the second interview may happen after the CTO interview)
If you work on an assignment, you can get a gift coupon, because we value your time.