ROMSについて

ROMSにご関心いただきありがとうございます。
まずは弊社コーポレートサイトより、会社・事業概要をご確認ください。

弊社は2019年に創業し、EC/小売り/物流事業者/メーカー様向けに高性能小型自動倉庫とロボットピックを中心とした小型自動化ソリューションを企画・開発・販売するスタートアップ企業です。

30㎡クラスの超小型無人店舗を祖業とし、その要素技術を活用して直近では物流センターや工場向けに業界最高効率の小型自動倉庫システム（NFC：Nano-Fuifillment Center）をはじめ、立体高速ピース仕分機（Nano-Sorter）やロボットピッキングシステム等を全て自社で開発し展開しています。

2022年9月にKDDI様と渋谷にクイックコマース向けの無人店舗RCS（Robotics Convenience Store）を開店、総額12億円の資金調達を完了、23年2月には平和島にラボを開設し、本格的にEC/物流事業者/メーカー様向けの倉庫内物流の自動化領域へ展開を開始しました。以下、掲載記事ご参照ください。

• Logistics Today記事
• LNEWS記事
• MHジャーナル記事

特に物流向けのソリューションとして、以下動画のNano-SorterやNano-Streamを矢継ぎ早に開発、展開を開始しており、2024年に複数社への導入が決定、今後1-2年を目途に海外へも事業展開をしていく計画です。また、市場への浸透を加速すべく新たなプロダクト開発も常に行っており、展示会やセミナー等で積極的に打ち出していく予定です。

• Nano-Sorter動画
• Nano-Stream動画

About ROMS

Thank you for your interest in ROMS.
First, please check our company and business profile on our corporate website.
☞https://roms.inc/

We are a start-up company established in 2019, planning, developing, and selling high-performance small automated warehouse solutions and robot picking systems for e-commerce/retail/logistics/manufacturers.

Although we started with the development of ultra-compact autonomous stores in the 30㎡ class and, utilizing its elemental technologies, we have recently developed the industry's most efficient compact automated warehouse system for distribution centers and factories, as well as 3D high-speed piece sorting machines and robot picking systems, all in-house.

In September 2022, we opened an unmanned store for quick commerce, RCS (Robotics Convenience Store), in Shibuya with KDDI and completed a total of 1.2 billion yen in funding. In February 2023, we opened a laboratory in Heiwajima and started expanding to the area of warehouse automation for logistics, e-commerce, and manufacturers.

We already plan to implement our solutions for several companies in Japan and expand our business overseas in the next 1-2 years. We are also developing new products to accelerate market penetration, which we plan to actively promote at exhibitions and seminars this year.

Why ROMS?

• Build a platform that modernizes warehouse and logistics operations through robotics, automation, data, and AI—helping customers improve throughput, accuracy, and operational efficiency.
• Learn from teammates who have led large-scale system development in major manufacturing and enterprise environments.
• Join from the planning stage and own the full lifecycle: problem discovery → design → development → evaluation → rollout and iteration.
• Work cross-functionally with product, business, and hardware/automation teams as needed to ensure AI solutions fit real-world operational constraints and deliver measurable impact.
• Move fast with high ownership: we build, ship, learn from customer feedback, and improve in short cycles.

Job Description

■Role summary：

As an AI/ML Engineer on our Data Science team, you will lead the development of AI models, analytics, proposals, and tools that improve warehouse and logistics operations for customers. 
Our data science work falls into two categories:

• Operational optimization for ROMS automation solutions like NFC / Nano-Stream / Nano-Sorter / RCS (e.g., inventory management, workload/demand forecasting, operational planning, decision support)
• Standalone AI software products, such as Packing Assistant AI

■Data you will handle (examples)：

• Real-time operational data with 10,000+ orders per day
• Real-time inventory and stock movement data
• Shipping and fulfillment data (picking/packing/shipping events)

■What you will work on：

• ML (tabular & time series): forecasting, classification, anomaly detection, recommendations
• Optimization: planning/allocation (e.g., packing-related optimization, inventory allocation)
• LLM-based AI: multi-agent workflows, RAG, and automation of operational decision-making
• Descriptive analytics / BI: KPIs, dashboards, root-cause analysis, reporting

Responsibilities

• Build analytics, decision-support tools, and AI/ML services that improve warehouse operations
• Design, develop, evaluate, and operate related systems and internal tools in production
• Collaborate with cross-functional teams (Business Development, Automation/Robotics engineers etc.)
• Contribute to team development (ways of working, hiring/interviews, mentoring)

Tech stack / Development environment

We focus on solid engineering fundamentals and production-ready delivery. Specific tools may vary by project; examples below reflect our typical stack.

• Core ML / DS: Python; common ML frameworks such as scikit-learn and deep learning frameworks (PyTorch / TensorFlow)
• Data & Analytics: SQL databases (e.g., PostgreSQL, MySQL); NoSQL databases (e.g., DynamoDB, MongoDB); BI / visualization tools (any major platform); analytics warehouses / OLAP (e.g., Redshift)
• Data Engineering / Orchestration: workflow/DAG orchestration (e.g., AWS Step Functions, Apache Airflow); building and operating data pipelines; streaming/messaging (e.g., Kinesis, Kafka)
• Cloud / Platform: we primarily use AWS, but experience with GCP/Azure is also welcome
  Engineering & Collaboration: containerization and CI/CD practices (e.g., Docker); version control and documentation tools (e.g., GitHub)

Skills

Required

• Strong ownership mindset: you proactively build, improve, and take initiative
• 3+ years of hands-on software development experience in Python (or equivalent), including production-grade implementation
• Practical experience applying ML/AI libraries to solve real business problems
• Interest in logistics / warehouse operations and automation-driven workflows (retail domain knowledge is a plus)

Welcomed

• Experience building optimization models and applying them to real operations
• Experience building LLM-based solutions (evaluation, RAG, agents/multi-agent workflows, and production guardrails)
• Experience with BI tools and communicating insights through dashboards/visualizations
• Experience with workflow orchestration and scalable data pipelines (e.g., Step Functions, Airflow)
• Experience operating data/ML systems on cloud platforms (we mainly use AWS)

Language / Team

We are an international team.
The company’s primary language is Japanese, while our team uses a lot of English in day-to-day work.
Communication is often mixed Japanese/English since not everyone is fluent in both.
You should be fluent in either Japanese or English, and comfortable collaborating in a bilingual environment.