Recommendation Engine Developer, Hourly (Grayjay)
We are currently interviewing engineers to contribute recommendation engines for the Grayjay media application. The work is hourly and can be performed on a part or full-time basis.
Grayjay aims to introduce a feature that recommends creators/videos to users based on their interests. The initial task involves developing an algorithm to tag channels in a way that correlates them with similar channels (possibly in a vector space). These tags could be based on:
- Channel information
- Titles/thumbnails from N pages of videos
- Descriptions and subtitles from M videos
The amount of required information should be minimized but we want statistics showing the minimization is done in a warranted manner.
Project Goals:
- Determine which metrics are most effective for accurately labeling a channel with minimal data.
- Produce a paper detailing the findings, with well-supported statistical evidence.
Interview Process:
- We will assess your expertise in statistics, machine learning, and algorithms.
- Please submit any research papers where you are the primary author, along with your hourly rate, your motivation, and your suitability for this role.
We are looking for individuals who are innovative, self-motivated, and ready to contribute to our projects. If you’re interested in either role, please reach out with the required information. To apply, please email jobs@futo.org with a resume and portfolio, mention the job title “Recommendation Engine Developer” in the email title.
