【募集の背景 / Purpose & Scope】

As a DevOps Engineer specializing in MLOps & GenAI Ops, you'll own the full lifecycle of AI models and cloud-native applications—from high-level strategy and process design through hands-on implementation and ongoing maintenance. You'll partner with data science, development, and product teams to design and optimize end-to-end workflows that make experiments reproducible, deployments (both model inference and frontend/backend services) scalable, release and rollback processes streamlined, and overall operations reliable, secure, and cost-efficient.

【職務の内容 / Essential Job Responsibilities】
(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.

(変更の範囲)

会社内での全ての業務

【就業環境に関する要件 / Specific Physical or Environmental Requirements】

At Astellas we recognize the importance of work/life balance, and we are proud to offer a hybrid working solution allowing time to connect with colleagues at the office with the flexibility to also work from home. We believe this will optimize the most productive work environment for all employees to succeed and deliver. Hybrid work from certain locations may be permitted in accordance with Astellas' Responsible Flexibility Guidelines.

【応募要件 / Qualifications】
<必須 / Required>

・ 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 / Preferred>
・ 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

【応募書類 / Application Documents】

和文履歴書・和文職務経歴書・英文レジュメ

Both Japanese and English Resumes are needed

【選考プロセス / Selection details】

書類選考 → 1次面接 → 2次面接 → 最終面接

※変更の可能性もございますので、予めご了承下さい。

CV screening → First interview → 2nd Interview → Final interview

• Please be advised that there might be a change in the process.

【勤務地 / Location】

(雇入れ直後)

東京都中央区 アステラス製薬 日本橋事業所 本社

Nihonbashi, Tokyo

(変更の範囲)

会社の定める事業場および自宅

【勤務開始日 / Start Date】

応相談

Will be decided according to the candidate's flexibility

【契約期間 / Contract Duration】

期間の定めなし

Not limited to specified period

【試用期間 / Probation Period】

試用期間原則なし

No probation period in principle

【給与 / Salary】

①基本給:当人の経歴・技術・技能等を考慮して決定

②裁量労働制の場合:裁量労働手当として職務グレードに応じて50,000~100,000円支給

③フレックスタイム制の場合:月間の所定労働時間を超えて勤務する時間に対して時間外勤務手当を支給

①Base salary: will be decided by the candidate's experience, skill and capability.

②When Discretionary Work System is applied: Discretionary work allowance will be paid.(50,000~100,000yen, based on the Grade)

③When Flextime System is applied: Overtime allowance will be paid for time worked in excess of prescribed working hours.

【昇給 / Salary Raise】

有り

【賞与 / Bonus】

有り

【諸手当 / Allowance】

裁量労働手当、住宅手当、通勤手当 等

Discretionary work allowance, Housing allowance, Commutation allowance, etc.

【勤務時間 / Working Hours】

8:45~17:45(月~木)、8:45~16:00(金)、企画業務型裁量労働制

裁量労働制の場合、所定労働時間を働いたものとみなす

8:45~17:45(Mon~Thu)、8:45~16:00(Fri)

Discretionary Work System

【休日 / Holidays】

完全週休2日制(土曜・日曜)、祝日、5月1日、夏季、年末年始

Weekends(Sat and Sun), holidays, May 1st, summer vacation, New Year holidays

【休暇 / Vacation Leave】

年次有給休暇、育児休業制度、介護休業制度 等

Annual paid leave, childcare leave system, nursing care leave system, etc.

【福利厚生 / Welfare】

雇用保険、労災保険、厚生年金、健康保険、共済会制度、社宅制度、持株会制度、財形貯蓄制度 等

Employment Insurance, Industrial Accident Compensation Insurance, Welfare Pension Insurance, Health Insurance, Mutual Aid Association System, Company Housing System, Employee Shareholder Association System, Property Accumulation Savings System

【アステラス製薬 採用サイト/ Career web site】

https://re-

For more information about Astellas, please visit our career web site.

"We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, or any other characteristic protected by law."