DevOps Engineering

募集要項

仕事内容

（雇入れ直後）
・ Pipeline Design & Automation
Architect, implement, and maintain CI/CD pipelines for data preprocessing, model training/validation, containerized inference stacks, and web applications (frontend/backend).
Manage pipelines to build, test, and deploy Docker containers and underlying infrastructure (e.g., Terraform, ARM templates) using automation frameworks (e.g., Azure DevOps Pipelines, Jenkins, GitLab CI).
・ Release & Rollback Strategy
Design and document streamlined release, rollback, and branching strategies, including approval gates, version tagging, and canary or blue-green deployments.
Collaborate with Product Managers and cross-functional teams to align release roadmaps, define milestones, and ensure smooth, predictable rollouts.
・ Infrastructure Provisioning & Management
Define and manage infrastructure as code to provision compute (CPU/GPU) and storage resources in cloud or hybrid environments, using tools like Terraform, optimizing cost, performance, and reliability
・ Containerization & Orchestration
Package models and services into containers (e.g., Docker) and deploy them on orchestration platforms such as Kubernetes, or serverless compute offerings
・ Model Versioning & Governance
Implement version control for code, data, and model artifacts using MLflow, or similar; maintain a model registry and enforce best practices for lineage, reproducibility, and rollback.
・ GenAI Ops & RAG Pipelines
Deploy and manage inference stacks for large language models and multimodal AI; integrate vector databases to support RAG workflows.
・ Monitoring, Alerting & Reliability
Define SLIs/SLOs, establish real-time monitoring for performance, latency, data drift, and concept drift; set up alerting and incident response processes
・ Security & Compliance
Enforce secure design and deployment practices, managing secrets, access controls, and network policies; ensure adherence to data-privacy regulations (e.g., GDPR, HIPAA) and internal standards.
・ Collaboration & Documentation
Work closely with Data Scientists, ML Engineers, and Product stakeholders to scope projects, plan releases, and troubleshoot issues; produce clear runbooks, architecture diagrams, and “infrastructure as code” documentation.

応募条件

【必須事項】

・ BS/MS in Computer Science, Engineering, or related field (or equivalent experience).
・ 3+ years in a DevOps/SRE/Platform Engineering role, with 1-2 years focused on MLOps or GenAI operations
・ Hands-on with Infrastructure as Code: Azure Resource Manager, Terraform
・ Solid scripting/programming skills in Python; familiarity with Bash or PowerShell
・ Strong proficiency in Linux, Docker, and Kubernetes
・ Production deployments on any cloud service
・ Understanding of RAG pipelines and vector databases
・ Experience with Software Monitoring
・ Excellent communication: able to translate between data science and operations teams
・ Mentored junior engineers and driven best-practice adoption

【歓迎経験】

・ Experience with Azure DevOps (Pipelines, Repos, Artifacts) or similar
・ Facility with ML lifecycle tools: MLflow, W&B, Kubeflow, Azure ML Pipelines
・ Familiarity deploying LLMs via Azure OpenAI, Hugging Face, or similar
・ Experience fine-tuning and serving ML and LLMs at scale
・ Familiarity with emerging GenAI orchestration frameworks
・ Benchmarking high-throughput inference systems and optimizing latency of solutions

【免許・資格】

【勤務開始日】

応相談

学歴

大学卒以上

雇用形態

正社員

試用期間

試用期間原則なし

勤務地

転勤の有無

転勤なし

受動喫煙防止措置

屋内禁煙

勤務時間

フレックスタイム制
フルフレックス（コアタイムなし）
本社：8:45～17:45（月～木）、8:45～16:00（金）

勤務開始日

応相談

休日休暇

完全週休2日制
年間有給休暇：　
法定休暇：年次有給休暇、産前産後休暇、介護休暇
特別休暇：夏季休暇、年末年始休暇
その他休暇：祝日、5月1日　育児休業制度

年収・給与

年収　　800万円～　経験により応相談

諸手当

裁量労働手当、住宅手当、通勤手当　等

昇給

あり

賞与

あり

採用人数

若干名

待遇・福利厚生

通勤手当：有
寮・社宅：有
住宅手当：有

各種制度

雇用保険：有
労災保険：有
厚生年金：有

選考プロセス

１）書類選考
２）一次面接
３）二次面接
４）最終面接