POWERD LAB の求人一覧 - 株式会社パワーエックス

■Engineering & Research Division / AI Data Center DC Block Architect ■About the role We are seeking an experienced AI Data Center DC Block Architect to join our team. In this role, you will be responsible for designing, developing, and optimizing modular, pre-engineered DC blocks that are tailored to support our organization's growing AI and machine learning workloads. ■Job Scope 1. AI Workload Analysis and Requirements: - Assess the organization's current and future AI and machine learning requirements, including compute, storage, and networking needs. - Collaborate with data science and IT teams to understand the specific performance, scalability, and reliability requirements of the AI workloads. - Identify any unique hardware or software considerations for the AI DC blocks, such as the need for specialized accelerators or optimized software stacks. 2. DC Block Architecture and Design: - Design modular, pre-engineered DC blocks that can efficiently support a variety of AI and machine learning workloads. - Ensure the DC block architecture is scalable, resilient, and aligned with industry best practices and the organization's overall data center strategy. - Optimize the DC block layout, power, cooling, and infrastructure to maximize performance, energy efficiency, and density. 3. Hardware Selection and Integration: - Evaluate and select the appropriate server hardware, including CPUs, GPUs, and specialized AI accelerators (e.g., NVIDIA Tensor Core GPUs, Google TPUs). - Determine the optimal storage solutions, considering factors like capacity, performance, and data redundancy (e.g., high-performance SSDs, NVMe, network-attached storage). - Integrate the networking infrastructure to support the required bandwidth, low-latency communication, and data transfer requirements of the AI workloads. 4. Software Stack Development and Optimization: - Design and develop the software stack for the AI DC blocks, including the operating system, containerization platform, and orchestration tools. - Integrate and configure leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras) to enable efficient model development and deployment. - Implement data management and processing pipelines, leveraging tools like Apache Spark, Hadoop, or custom data ingestion and preprocessing workflows. - Optimize the software stack for performance, scalability, and resource utilization to ensure the AI DC blocks operate at peak efficiency. 5. Monitoring and Observability: - Develop comprehensive monitoring and observability capabilities for the AI DC blocks, including metrics, logging, and tracing. - Implement data-driven insights and analytics to identify performance bottlenecks, optimize resource allocation, and ensure overall system reliability. - Automate deployment, scaling, and management processes to streamline the operation and maintenance of the AI DC blocks. 6. Security and Compliance: - Incorporate robust security measures, such as access controls, network segmentation, and data encryption, into the AI DC block design. - Ensure compliance with relevant data privacy and regulatory requirements (e.g., GDPR, HIPAA) by implementing appropriate data governance and access policies. - Develop and test disaster recovery and business continuity plans to ensure the resilience of the AI DC blocks in the event of failures or disasters. 7. Continuous Optimization and Scalability: - Continuously monitor the performance and resource utilization of the AI DC blocks to identify opportunities for optimization. - Implement auto-scaling and dynamic resource allocation mechanisms to handle fluctuations in AI workload demands. - Explore options for distributed or federated learning architectures to scale the AI capabilities across multiple edge devices or smaller data centers. ■Internal common IT tools - Google Workspace （Gmail, G-cal, Gmeet等） - Slack - Notion - Dialpad - SmartHR - Money Foward - Bakuraku etc. ■About Engineering and Research Division Our Engineering and Research Division consists of mainly three teams that handle end-to-end development of Hardware and software systems for Energy storage & power transfer solutions and services. Currently, approximately 50 specialists are engaged in the mission of advancing energy storage technologies and solutions. The Division is organized into the following teams: - Series Development: Responsible for prototyping, testing & validation , requirements engineering , series handover of new products including product support and commissioning. - Advanced Engineering: Responsible for development and experimentation into emerging technologies to sustain our current and future roadmap of energy solutions with focus on a areas viz. embedded development, PCB design, model based development, battery management, power conversion, digital twins, edge computing, cloud solutions ,AI/ML based dispatch optimization, generation and forecasts. - Product Lifecycle Management: Manages product & project life cycles by tracking across quality gates through development, sourcing, value engineering leading up to manufacturing and after sales activities through cross functional coordination and data intensive product life cycle assessment Working alongside talented engineers from around the world, you will have the opportunity to thrive in a diverse environment that values autonomy and empowers individuals to make effective contributions while gaining new skills and experiences on some of the latest emerging technologies directly applied into our solutions.

■Engineering & Research Division / AI Data Center Architect ■About the role We are seeking an experienced AI Data Center Architect to join our team. In this role, you will be responsible for designing, implementing, and optimizing a medium-sized AI data center that leverages the latest hardware and software technologies to support our organization's growing AI and machine learning workloads. ■Job Scope 1. AI Data Center Architecture and Design: - Assess the organization's current and future AI and machine learning requirements, including compute, storage, and networking needs. - Design a scalable, resilient, and efficient AI data center architecture that can accommodate a variety of AI workloads, such as model training, inference, and data processing. - Ensure the architecture aligns with industry best practices, regulatory compliance, and the organization's IT and business strategies. 2. Hardware and Infrastructure Selection: - Evaluate and select the appropriate server hardware, including CPUs, GPUs, and specialized AI accelerators (e.g., NVIDIA Tensor Core GPUs, Google TPUs). - Determine the optimal storage solutions, considering factors like capacity, performance, and data redundancy (e.g., high-performance SSDs, NVMe, network-attached storage). - Ensure the networking infrastructure can support the required bandwidth, low-latency communication, and data transfer requirements. - Incorporate power and cooling considerations, such as efficient cooling systems and redundant power supplies, to maintain optimal operating conditions. 3. Software Stack Integration and Optimization: - Evaluate and integrate the appropriate operating system (e.g., Linux distributions), containerization platform (e.g., Docker, Kubernetes), and orchestration tools. - Integrate and configure leading AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras) to enable efficient model development and deployment. - Implement data management and processing pipelines, leveraging tools like Apache Spark, Hadoop, or custom data ingestion and preprocessing workflows. - Optimize the software stack for performance, scalability, and resource utilization to ensure the AI data center operates at peak efficiency. 4. Monitoring, Observability, and Automation: - Implement comprehensive monitoring and observability tools to track the performance, resource utilization, and health of the AI data center. - Develop data-driven insights and analytics to identify bottlenecks, optimize resource allocation, and ensure overall system reliability. - Automate deployment, scaling, and management processes to streamline the operation and maintenance of the AI data center. 5. Security and Compliance: - Implement robust security measures, such as access controls, network segmentation, and data encryption, to protect the AI data center from potential threats. - Ensure compliance with relevant data privacy and regulatory requirements (e.g., GDPR, HIPAA) by implementing appropriate data governance and access policies. - Develop and test disaster recovery and business continuity plans to ensure the resilience of the AI data center in the event of failures or disasters. 6. Continuous Optimization and Scalability: - Continuously monitor the AI data center's performance and resource utilization to identify opportunities for optimization. - Implement auto-scaling and dynamic resource allocation mechanisms to handle fluctuations in workload demands. - Explore options for distributed or federated learning architectures to scale the AI capabilities across multiple edge devices or smaller data centers. 7. Collaboration and Knowledge Sharing: - Provide technical leadership and mentor junior engineers on AI data center best practices and strategies. - Collaborate with cross-functional teams (data science, IT operations, security) to ensure the AI data center meets the organization's evolving needs. - Document and share knowledge, solutions, and lessons learned to promote continuous improvement within the organization. ■Internal common IT tools - Google Workspace （Gmail, G-cal, Gmeet等） - Slack - Notion - Dialpad - SmartHR - Money Foward - Bakuraku etc. ■About Engineering and Research Division Our Engineering and Research Division consists of mainly three teams that handle end-to-end development of Hardware and software systems for Energy storage & power transfer solutions and services. Currently, approximately 50 specialists are engaged in the mission of advancing energy storage technologies and solutions. The Division is organized into the following teams: - Series Development: Responsible for prototyping, testing & validation , requirements engineering , series handover of new products including product support and commissioning. - Advanced Engineering: Responsible for development and experimentation into emerging technologies to sustain our current and future roadmap of energy solutions with focus on a areas viz. embedded development, PCB design, model based development, battery management, power conversion, digital twins, edge computing, cloud solutions ,AI/ML based dispatch optimization, generation and forecasts. - Product Lifecycle Management: Manages product & project life cycles by tracking across quality gates through development, sourcing, value engineering leading up to manufacturing and after sales activities through cross functional coordination and data intensive product life cycle assessment Working alongside talented engineers from around the world, you will have the opportunity to thrive in a diverse environment that values autonomy and empowers individuals to make effective contributions while gaining new skills and experiences on some of the latest emerging technologies directly applied into our solutions.

■Engineering & Research Division / IoT Security(ZTN) / Cloud & Edge Security Engineer ■About the role We’re seeking a Security Engineer to implement Zero Trust architecture for our IoT-based battery storage systems. You’ll secure device onboarding, manage cloud IoT integration, enforce access policies, and develop secure applications. ■Job Scope - Design, implement, and manage zero trust architectures for IoT and edge devices. - Secure device onboarding, certification, and communication channels. - Develop and enforce access policies aligned with zero trust principles. - Integrate IoT platforms (Azure IoT, AWS IoT) with security tools. - Implement device management and remote update mechanisms. - Develop secure web applications for device management. - Monitor security posture and respond to threats. - Collaborate with cross-functional teams for scalable deployment and security compliance. ■Internal common IT tools - Google Workspace （Gmail, G-cal, Gmeet等） - Slack - Notion - Dialpad - SmartHR - Money Foward - Bakuraku etc. ■About Engineering and Research Division Our Engineering and Research Division consists of mainly three teams that handle end-to-end development of Hardware and software systems for Energy storage & power transfer solutions and services. Currently, approximately 50 specialists are engaged in the mission of advancing energy storage technologies and solutions. The Division is organized into the following teams: - Series Development: Responsible for prototyping, testing & validation , requirements engineering , series handover of new products including product support and commissioning. - Advanced Engineering: Responsible for development and experimentation into emerging technologies to sustain our current and future roadmap of energy solutions with focus on a areas viz. embedded development, PCB design, model based development, battery management, power conversion, digital twins, edge computing, cloud solutions ,AI/ML based dispatch optimization, generation and forecasts. - Product Lifecycle Management: Manages product & project life cycles by tracking across quality gates through development, sourcing, value engineering leading up to manufacturing and after sales activities through cross functional coordination and data intensive product life cycle assessment Working alongside talented engineers from around the world, you will have the opportunity to thrive in a diverse environment that values autonomy and empowers individuals to make effective contributions while gaining new skills and experiences on some of the latest emerging technologies directly applied into our solutions.

■Engineering & Research Division / DevOps/SRE(Site Reliability Engineer) ■業務内容 - Kubernetes・各種Cloud serviceを用いたサービス基盤の設計・構築・運用 - Bazelを用いた社内ビルドシステムおよびCI/CDの開発・運用 - プロダクト生産におけるネットワーク・ソリューション構築 - IoT ネットワーク・Deployシステムの設計・開発 ■本求人の魅力について - 蓄電池を利用した新しいサービスにおける高い信頼性を実現するといったチャレンジ - 優秀なSWEと働くことのできる環境 - 自らが設計・技術選択を行い進めていくことができる ■部署・チームについて - SRE/DevOpsチームでは、PowerXのサービスにおける重要な基盤を高いクオリティで実現し、より迅速に・スマートにビジネスを推進させるためのシステム開発・運用を行っています - PowerX Visionの実現のため、競争力の源泉となるサービス基盤・開発基盤を実現することができる優秀なソフトウェアエンジニアを求めています ■社内共通ITツール - Google Workspace （Gmail, G-cal, Gmeet等） -Slack -Notion -Dialpad -SmartHR -Money Foward -バクラク 等 ※英語を使う職場環境のため、ご応募の際に英文CVのご提出もお願いいたします ※英語力を伸ばしたい方も大歓迎です

■Engineering & Research Division / Full Stack Engineer ■Summary We are looking for an experienced Fullstack Software Engineer to lead the server-side development of our Energy Management System applications. This system serves as the intelligence behind our battery solutions, supporting automation and optimization of operations across various electricity markets. You will help design and implement robust, high-performance backend infrastructure that ensures scalability, reliability, and responsiveness. ■Job Scope - Design, develop, and maintain highly performant, reliable, scalable, and secure backend systems and server side logic for WebApp/ Mobile App/ Services pertaining to Energy management , Battery management , Charger management & Asset management - Oversee projects from conception to deployment, ensuring smooth execution and delivery to create a great and on-brand user experience. - Maintain and optimize the backend infrastructure to meet evolving project needs. - Collaborate with front-end developers to integrate user-facing elements with server-side logic. - Write clean, standardized, maintainable, testable, and reusable backend code to solve business and technical problems. ■Internal common IT tools - Google Workspace （Gmail, G-cal, Gmeet等） - Slack - Notion - Dialpad - SmartHR - Money Foward - Bakuraku etc. ■About Engineering and Research Division Our Engineering and Research Division consists of mainly three teams that handle end-to-end development of Hardware and software systems for Energy storage & power transfer solutions and services. Currently, approximately 50 specialists are engaged in the mission of advancing energy storage technologies and solutions. The Division is organized into the following teams: - Series Development: Responsible for prototyping, testing & validation , requirements engineering , series handover of new products including product support and commissioning. - Advanced Engineering: Responsible for development and experimentation into emerging technologies to sustain our current and future roadmap of energy solutions with focus on a areas viz. embedded development, PCB design, model based development, battery management, power conversion, digital twins, edge computing, cloud solutions ,AI/ML based dispatch optimization, generation and forecasts. - Product Lifecycle Management: Manages product & project life cycles by tracking across quality gates through development, sourcing, value engineering leading up to manufacturing and after sales activities through cross functional coordination and data intensive product life cycle assessment Working alongside talented engineers from around the world, you will have the opportunity to thrive in a diverse environment that values autonomy and empowers individuals to make effective contributions while gaining new skills and experiences on some of the latest emerging technologies directly applied into our solutions.

■業務内容 - 製品開発のためのサプライヤー開拓活動 - 社内外とのコスト、リードタイムなどの交渉および調整 - ラボでの必要部材の在庫・発注業務管理など ■社内共通ITツール - Google Workspace （Gmail, G-cal, Gmeet等） - Slack - Notion - Dialpad - SmartHR - Money Foward - バクラク 等