Senior Machine Learning Engineer／Engineering Dept.English summary from Japanese

サグリ株式会社

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Salary

Negotiable ＜Scope of change: All assignments are subject to reassignment (including transfers to other companies).

Location

◆Tokyo Head Office Room 507, Cross Office Shinjuku, 1-12 Nishi-Shinjuku 7-chome, Shinjuku-ku, Tokyo 160-0023 ◎Nearest Stations Toei Oedo Line: “Shinjuku-Nishiguchi” Station, 1-minute walk from Exit D5 JR Lines / Keio Line / Keio New Line / Odakyu Electric Railway / Tokyo Metro Marunouchi Line / Toei Shinjuku Line / Toei Oedo Line: “Shinjuku” Station, West Exit (5-minute walk) Seibu Shinjuku Line: “Seibu Shinjuku” Station (5-minute walk) <Regarding the Scope of Assignment Changes> Immediately after hiring: As specified in the job posting Scope of changes: Assignment transfers to all types of duties are possible (including secondments while remaining on the company’s payroll)

Job Type

Full-time

Work Style

Working hours Flextime system introduced (with core hours) Start time: 6:00 - 10:00 End time: 15:00 - 22:00 Core hours: 10:00 - 15:00 Break time: 1 hour Holidays More than 120 days off per year In principle, 2 days off per week (Saturday and Sunday), national holidays

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Role summaryEnglish summary from Japanese

English summary for screening — check the original posting before applying.

We are seeking a Senior Machine Learning Engineer to develop ML components for an innovative MRV and decarbonization platform. This role involves integrating AI, satellite remote sensing, and carbon footprint tracking for agricultural enterprises, government agencies, and farmers.

Must-haves

5+ years of experience as ML Engineer or Data Scientist, with 2+ years in a leadership role
Strong proficiency in Python
Experience with cloud platforms (AWS)
Experience with satellite image processing and geospatial data analysis
Experience tech leading cross-team engineering efforts
Strong software engineering practices
For Tokyo-based positions: Business-level Japanese proficiency

Nice-to-haves

Experience with or understanding of satellite-based remote sensing and agriculture
Knowledge of microservices architecture
Experience with database systems (RDBMS/NoSQL)
Familiarity with monitoring systems, logging, operations, and SLO/SLA concepts
Experience working in AgriTech or environmental sustainability sectors

Tech stack

PythonTypeScriptTensorFlowPyTorchAWSGitGitHubJIRASlackNotion

Work style

Tokyo Head Office. Flextime system (core hours 10:00-15:00). More than 120 days off per year, typically Sat/Sun.

Other notes

Salary is negotiable. All assignments are subject to reassignment.

About the Company