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Required Software Intern (Malshab)
As a Software Intern (Malshab), you will:
Take a central role in advancing the features and infrastructures of one of our core products
Collaborate closely with multiple teams to analyze, develop and implement new workflows and features
Troubleshoot and debug complex flows while finding and implementing creative solutions.

We are looking for a highly organized and detail-oriented Intern to join our Operation & Maintenance team at Sungrow Israel.
This is a full time back office intern position focused on computer-based work, supporting the daily operations of the team, including CRM and service request management, scheduling and coordination of field activities, documentation, reporting, and administrative support for our Energy Storage System projects.
The role requires strong organizational skills, ownership, and the ability to manage multiple tasks and interfaces simultaneously while ensuring smooth operational flow behind the scenes.

Responsibilities:
1. Back Office and Administrative Support:
Providing administrative support to the service team, including coordination, follow-up on open tasks, documentation, reports, and maintaining accurate records according to internal procedure.
2. Issue Routing and Follow:
Identifying system alerts, routing them to the relevant internal expert, and following up to ensure issues are handled and closed in a timely manner. You do not fix technical problems; you manage the flow.
3. Scheduling & Coordination:
Managing calendars, maintenance activities, deadlines, and internal scheduling to ensure tasks are completed on time and properly coordinated.
4. Data & System Monitoring:
Collecting and reviewing operational data from Energy Storage System plants, monitoring system performance, and identifying irregularities to ensure accurate documentation and follow-up.

*Part-Time or Full-Time Opportunity

Responsibilities:
The research focuses on designing next-generation rack and SuperPod architectures that combine elasticity through resource pooling with optimal performance enabled by holistic co-design across applications, parallel programming models, interconnect fabrics, and compute, memory, and switch chip architectures. On the communication side, the work architects scalable, high-bandwidth, and low-latency scale-up fabrics across multiple chips at rack and SuperPod scale. On the memory side, it explores richer protocol semantics beyond traditional load/store operations to reduce unnecessary data movement and rethinks memory hierarchies to expose large-scale capacity with near-local latency. On the compute side, it analyzes the requirements of General Compute and Generative AI workloads and their parallel programming models to fully leverage large-scale system resources.
Investigate and prototype new architectural features, including but not limited to:
o Tiered Memory: Explore advanced memory organizations, including hardware-managed caching, to enable software-transparent, fine-grained promotion and demotion of cache lines across the memory hierarchy.
o Prefetching/Speculation: Evaluate and design existing and next-generation hardware prefetching and speculation mechanisms to effectively hide local and remote memory latencies at rack and SuperPod scale.
o Near-Memory/Network Processing: Develop support for key primitives executed at the memory and network layers to minimize unnecessary data movement across sparse, dense, and pointer-based data structures.
o Workload-Centric Co-Design: Study optimal parallelization strategies at rack and SuperPod scale for both General Compute and Generative AI workloads, and design dedicated hardware support for widely used parallel programming primitives such as RPCs and collective communication.
Write reports and papers on the research results and present them.