株式会社エキュメノポリス
生成AI活用企業
【Stock Options/DeepTech/Conversational AI/English Required】MLOps Engineer | AI Platform Handling Dialogue Data
最終更新日:
企業情報をみる職種
機械学習エンジニア/テックリード年収
600万円 〜 1,100万円利用技術
こだわり条件
生成AIの活用状況
最終更新日:2025-06-03最新の情報についてはカジュアル面談や選考の中で確認ください。
生成AI技術/ツールの導入・活用状況
生成AIモデルの開発・LLM技術の研究開発を行っているプロダクト/サービスへの組み込みを実施・推進している社内活用による業務効率化を目的に導入・活用している
開発組織において公式に導入・活用されているAIツール・機能・技術
仕事内容
Job Details
As an MLOps / Machine Learning Engineer, you'll collaborate closely with research member
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開発環境
Development Environment
MLOps Team (Total 6 members, including contractors)
・PdM: 2
・Engineering Manager: 1
・Researcher: 1
・Full-stack Engineer: 2 members
Tech Stack
・ML: Python
・Backend: Typescript, Python
・Infrastructure: GCP, Terraform, Docker, Packer, etc.
・Others: GitHub, Slack, Miro, Figma, Notion, Sentry, etc.
・Coding Agent: Devin, GitHub CoPilot
*We are also planning new product development, where technology selection will be made from scratch.*
*You don't need to be proficient in all of the above tech stack.*
求めるスキル
必須スキル/経験
Required Skills
・Business-level Japanese and English proficiency
・Practical experience in machine learning model development
・Experience designing and building MLOps infrastructure (e.g., optimizing data collection/annotation, managing training/evaluation, automating deployment/monitoring)
・Experience designing and implementing CI/CD pipelines
・Experience building environments for stable model deployment
・Experience implementing machine learning workflows using Python
・Experience with infrastructure technologies** such as GCP, Terraform, and Docker
*We are looking for candidates with a combination of these experiences.
歓迎スキル/経験
Preferred Skills & Experience
・Deep knowledge of the ML domain
・Experience building model training platforms or data infrastructure
・Experience in web application development and maintenance (around 2-3 years)
・Ability to independently identify challenges and translate them into product solutions
・Strong communication skills to actively engage with internal and external teams and ensure smooth communication
・Ability to propose, discuss, and execute projects in DevOps
・Experience acting as a bridge between researchers and engineering teams
求める人物像
Desired Candidate Profile
・Actively communicates with internal and external teams to ensure smooth information exchange
・Manages projects with a strong awareness of deadlines
・Comfortable in a startup environment and possesses flexibility
・Eager to actively participate in systematizing previously researcher-managed processes and building machine learning infrastructure
仕事の魅力
Why join us?
■Overview
Equmenopolis, established in May 2022 as a spin-off from Waseda University's Conversational AI Media Research Group, is a university-launched startup planning and developing "EQU AI Platform." This cutting-edge conversational AI diagnostic platform enables ability assessment and growth support through natural dialogue.
The "EQU AI Platform," built on patented technology, creates a dialogue process that generates insights" and changes beyond traditional Q&A evaluations. Our AI real-time captures emotions and intentions, context and appropriateness of responses, and provides optimal feedback and learning support to users.
The platform was officially introduced into Waseda University's regular English conversation classes in 2023. Furthermore, in March 2023, we were the sole East Asian finalist to present at "SXSW EDU Launch," an educational startup pitch competition at SXSW (South by Southwest), a world-renowned creative event, significantly boosting our global recognition.
As our services expand, we're looking for teammates to innovate the future of language education with us. Our team comprises members with diverse backgrounds, from multimodal dialogue systems, natural language processing, and second language acquisition to learning science, digital humans, quantum computing, and media art. Our team members also come from various countries, including Japan, the US, the UK, Spain, and Poland.
■Background of Recruitment Expansion
We're strengthening our organization and building a robust technical foundation to diversify our business:
1. Developing conversational AI agents for diagnostic evaluation and learning support as a PaaS, providing an application development environment that caters to diverse needs for conversational diagnostics
2. Advancing technology that integrates and utilizes multimodal data (voice, text, gaze, facial expressions, dialogue structure) to comprehensively evaluate and diagnose dialogue flow, appropriateness, and "interaction skills"—aspects that were challenging with conventional language evaluation systems
3. Generalizing the foundational technology cultivated with "LANGX Speaking" to expand into a broader language education market beyond English conversation learning, as well as specialized fields such as corporate training, customer support, and healthcare. Specifically, in the near future, we plan to develop self-learning Japanese applications tailored for specific industries for foreign learners.