Machine Learning Developer

Hacarus Inc.

Kyōto-shi, Japan
Japan, 〒604-8206 Kyōto-fu, Kyōto-shi, Nakagyō-ku, Machigashirachō, 112, 菊三ビル
Kyōto-shi
Kyōto-fu
Japan
Japan
TELECOMMUTE
Penuh waktuFULL_TIME

Berakhir 7 years ago

2017-07-28T16:00:00+00:00

Ditutup.

Deskripsi Pekerjaan

As a Machine Learning Engineer, you will develop various functionalities using machine learning algorythm to provide excellent experience in our healthcare service. You are also supposed to build and maintain data engineering platform to collect and store required information for machine learning system.

Working in a cross-functional scrum team with the Project Manager and BackEnd Engineers, you will work on product requirements and software concepts and actively create the next generation of our machine learning system.

Kualifikasi Minimum

Experience of AWS or other cloud services would be a plus.
Over 3 years experience in building application using machine learning algorythm.
Good knowledge of numerical and scientific computation with Python and popular machine learning libraries.
Your written and spoken English is excellent.

Fasilitas dan Tunjangan

Medical / Health Insurance
Paid Holidays
Work from Home

Lain-Lain

Reimbursement for conference, book and technical training fees

Jurusan yang Diminati

Information Technology

Ringkasan Perkerjaan

Tingkat Posisi: Supervisor / Asisten Manager

Spesialisasi: IT and Software

Persyaratan tingkat pendidikan: Lulus program Sarjana (S1)

Respon rekruter ke lamaran: Sometimes

Alamat Kantor: Kikusan Bldg. 3F Room 302 112 Machigashiracho Nakagyo-ku, Kyoto-shi, Kyoto, Japan

Industri: Information Technology / IT

Lowongan: 1 lowongan dibuka

Situs: http://hacarus.com

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Tentang Hacarus Inc.

Hacarus started out in 2014 as a healthcare AI venture, with a mission to achieve health and a long life through a nutritious diet. From the beginning, we used AI technology (artificial intelligence) to optimize food and nutrition balance on an individual level. Our main differentiation is our Sparse Modeling methodology, which works efficiently with small amounts of data. That’s why we call our approach Small Data AI. We believe that, in the long term, increasing the availability of proprietary technologies helps to advance the human condition, reducing poverty and inequality in the world. Distributing our Sparse Modeling AI to firms creates greater efficiency and productivity in society. In practicality, this translates to being able to better diagnose diseases, learn useful medical insights, and bring cheaper products to consumers through efficient manufacturing practices. Looking to the future, we plan to extend our technology to an even greater number of sectors and applications to aid in making human lives healthier and longer.

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