グローバルでサービスを展開する大手外資系ITサービス企業でのAzure AI Architectの求人
求人ID:1343276
募集継続中
転職求人情報
職種
Azure AI Architect
ポジション
担当者〜
年収イメージ
応相談(経験・能力を考慮の上当社規定により決定)
仕事内容
【Responsibilities】
・Envision, build, deploy and operationalize an end-to-end machine learning (ML) and AI pipeline
・Build a robust enterprise wide architecture for AI and collaborate with data scientists, data engineers, developers, operations and security
・Perform the following functions,
-Requirement analysis: Analyzing what an organization needs and how AI can help.
-Solution design: Designing AI solutions that are scalable, cost-effective, and in alignment with the organization’s goals.
-Technology selection: Selecting the appropriate technology stack and tools that will be used to build the AI system.
-Auditing: Conducting a comprehensive audit of AI tools and practices, including data, models, and software engineering, emphasizing continuous improvement. Establishing a feedback loop to evaluate AI services, facilitate model recalibration, and retrain models as needed.
-Implementation: Overseeing the implementation of the AI system and ensuring it meets the organization’s requirements.
-Monitoring and maintenance: Monitoring the performance of the AI system, troubleshooting issues, and ensuring the system is maintained and updated regularly.
・Has a holistic understanding of the business landscape, combined with a grasp of AI capabilities, allowing them to guide AI projects towards success
・To work in team collaboration with cross-functional teams, including technical architects, data engineers, and domain experts, to understand business requirements and develop effective AI solutions
・To be diligent in learning / scaling up in the areas of Data Science-AI with self-initiative towards career excellence
・Envision, build, deploy and operationalize an end-to-end machine learning (ML) and AI pipeline
・Build a robust enterprise wide architecture for AI and collaborate with data scientists, data engineers, developers, operations and security
・Perform the following functions,
-Requirement analysis: Analyzing what an organization needs and how AI can help.
-Solution design: Designing AI solutions that are scalable, cost-effective, and in alignment with the organization’s goals.
-Technology selection: Selecting the appropriate technology stack and tools that will be used to build the AI system.
-Auditing: Conducting a comprehensive audit of AI tools and practices, including data, models, and software engineering, emphasizing continuous improvement. Establishing a feedback loop to evaluate AI services, facilitate model recalibration, and retrain models as needed.
-Implementation: Overseeing the implementation of the AI system and ensuring it meets the organization’s requirements.
-Monitoring and maintenance: Monitoring the performance of the AI system, troubleshooting issues, and ensuring the system is maintained and updated regularly.
・Has a holistic understanding of the business landscape, combined with a grasp of AI capabilities, allowing them to guide AI projects towards success
・To work in team collaboration with cross-functional teams, including technical architects, data engineers, and domain experts, to understand business requirements and develop effective AI solutions
・To be diligent in learning / scaling up in the areas of Data Science-AI with self-initiative towards career excellence
必要スキル
●Required
- Bachelor’s degree in Computer Science, Software Engineering, or related fields (equivalent practical experience also acceptable)
- 5+ years of practical experience in designing and developing AI platforms (Azure is preferred)
- Ability to communicate at a business level in both English and Japanese, and to collaborate with internal and external stakeholders
●Nice to have
- Deep understanding and practical experience in AI-related technologies such as machine learning, deep learning, natural language processing, and computer vision
- AI architecture and pipeline planning. Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.
- Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
- Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow), ML techniques (such as random forest and neural networks) and developing large-scale models using AI frameworks such as TensorFlow, PyTorch, and Keras
- Experience in designing and developing AI systems using cloud platforms (Google, AWS, Azure, etc.)
- Knowledge of AI model operations and deployment (model optimization, monitoring, version control, etc.)
- Practical experience in large-scale data processing technologies (BigQuery, Spark, Hadoop, etc.)
- Knowledge of AI ethics and privacy, and ability to incorporate them into AI system design
●Language
Native level Japanese, ideally Business level English in reading, writing and speaking
- Bachelor’s degree in Computer Science, Software Engineering, or related fields (equivalent practical experience also acceptable)
- 5+ years of practical experience in designing and developing AI platforms (Azure is preferred)
- Ability to communicate at a business level in both English and Japanese, and to collaborate with internal and external stakeholders
●Nice to have
- Deep understanding and practical experience in AI-related technologies such as machine learning, deep learning, natural language processing, and computer vision
- AI architecture and pipeline planning. Understand the workflow and pipeline architectures of ML and deep learning workloads. An in-depth knowledge of components and architectural trade-offs involved across the data management, governance, model building, deployment and production workflows of AI is a must.
- Software engineering and DevOps principles, including knowledge of DevOps workflows and tools, such as Git, containers, Kubernetes and CI/CD.
- Data science and advanced analytics, including knowledge of advanced analytics tools (such as SAS, R and Python) along with applied mathematics, ML and Deep Learning frameworks (such as TensorFlow), ML techniques (such as random forest and neural networks) and developing large-scale models using AI frameworks such as TensorFlow, PyTorch, and Keras
- Experience in designing and developing AI systems using cloud platforms (Google, AWS, Azure, etc.)
- Knowledge of AI model operations and deployment (model optimization, monitoring, version control, etc.)
- Practical experience in large-scale data processing technologies (BigQuery, Spark, Hadoop, etc.)
- Knowledge of AI ethics and privacy, and ability to incorporate them into AI system design
●Language
Native level Japanese, ideally Business level English in reading, writing and speaking
就業場所
就業形態
正社員
企業名
グローバルでサービスを展開する大手外資系ITサービス企業
企業概要
グローバルでサービスを展開する大手外資系ITサービス企業
企業PR
数々のグローバル企業に価値をもたらしてきた、業界最高水準のITサービスやソリューションをお客様に提供します。
業務カテゴリ
組織カテゴリ
備考
応募ありがとうございました。コンサルタントからご連絡します
応募出来ませんでした。恐れ入りますがもう一度やり直してください
気になるに登録しました
気になるに登録出来ませんでした。恐れ入りますがもう一度やり直してください
この求人と似た求人情報
ITコンサルタントの求人情報
事業会社の求人情報
コンサルティングの求人情報
- 【石川】経営コンサルティング企業での戦略コンサルタント/~800万円/石川県
- ブティック系M&A、会計・税務コンサルファームでのIT戦略・ERPコンサルタント(マネージャー以上)/800万円~1600万円/東京都
- 戦略・業務・ITコンサルティングファームでのビジネスコンサルタント【未経験・ポテンシャル層向け】/~1000万円/東京都
- PwC Japan合同会社/監査およびアシュアランス、コンサルティング等のサービス会社での在宅秘書 (上越、北陸、東北新幹線沿線に居住の方対象)/~800万円/お問い合わせください。
- 日系大手コンサルティングファームにおける石油業界向けコンサルタント(ダイレクター、SMクラス)/1000万円~2000万円/東京都
転職体験記
- テクニカルスキルを活かして、リアルビジネスも手掛けるコンサルティングファームへ(40代/男性/私立大学卒)
- 事業会社から大手ITコンサルティング会社へ(50代/男性/私立大学卒)
- 大手Sierから金融 ・ 決済領域を中心とした事業開発を行う企業へ(20代/男性/私立大学卒)
- 新たなチャレンジ、大手監査法人へ(20代/女性/国立大学卒)
- ユーザー系システム子会社から「発注側支援」の大手ITコンサルティング会社へ(40代/男性/私立大学卒)
- 日系大手コンサルティングファームから上場コンサルティングファームへ(20代/男性/私立大学卒)
- リアルビジネスも手掛けるブティック系コンサルティング・ファームへ(40代/男性/私立大学卒)
- プロセス開発の経験を活かして日本を代表する電機・通信機器メーカーへ(40代/男性/国立大学院卒)
- 銀行システム関連業務の知見を活かして、ITコンサルティング企業へ(50代/男性/私立大学卒)
- 事業会社での経験を活かして、ソフトウェアの品質保証、テストサービスを主力事業とするIT企業へ(50代/男性/高等専門学校卒)