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We are a top global leader, manufacturing smart energy solutions. The company's broad range of products encompasses intelligent inverter and Storage systems & SST solutions; by doing that, we are changing the way electricity is being produced and consumed around the world. In this position you will be a part of component's team and deal with the qualification of electronic and electro-mechanical parts and in the failure analysis of failed parts. Component reliability team deals with challenges related to reliability of components in future products, products in mass production and help with analysis of components in products that failed in field.
What will you be doing in this position?
Prepare TEST plans, assemble TEST setups, collect data and summarize the results. Software Development of automated hardware tests, drivers, protocols ( C #/ Python ) Design and operate automatic testers and TEST setups to simulate operating life and reliability of the components. Analyze failed products or components to gain understanding of the physics of failure

Country:
Israel
City:
Herzliya

we are looking for a Hardware Test and Product Engineer.
The Test & Product team is responsible for keeping a target of a very aggressive cost limit of the production testing (wafer sort) while performing comprehensive testing of all the units functionalities. This involves:
Development of the tests using the Teradyne UF tester
Development of unique and advanced test HW
Monitoring and analyses the production data
FA (Failure Analysis) when issues are discovered
Innovative DFT (design for testability) with the design team

We are seeking a senior communication systems engineer to help develop the next generation of algorithms and standards that power this revolution.

We are looking for a brilliant system engineer to join Wiliot and help to scale the world of IoT.
As a system engineer, you will work on various innovative fields from RF automation, algorithms., channel usage optimizations, energy consumption optimization and dynamic network development.

we are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.
A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.
***This is not a Data Science position***
Responsibilities:
Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines

we are seeking a Lead System Architect to join our system architecture team and help define the next generation of our AI-SuperNIC scale-out chip.
AI scale-out communication is a critical element in modern data centers, and emerging standards such as Ultra Ethernet aim to address this challenge. This role focuses on defining a high-performance Smart NIC architecture optimized for GPU-centric AI workloads, with emphasis on low-latency, high-bandwidth data movement.
You will work across hardware and software domains, collaborating closely with AI, platform, driver, and VLSI teams to design a competitive scale-out networking solution.
Responsibilities:
Define product requirements and architecture for next-generation ultra low-latency AI-SuperNIC
Design end-to-end data paths across NIC, host, and GPU memory, with focus on GPU connectivity (PCIe, NVLink, CXL)
Lead adoption of emerging standards such as UEC and UALink, while maintaining compatibility with existing ecosystems
Establish architecture guidelines and partitioning across hardware, firmware, and software
Drive performance modeling, analysis, and system-level optimization for AI workloads
Optimize scale-out communication patterns (e.g., collectives) for GenAI training and inference
Collaborate with software teams on drivers, runtimes, and integration with AI frameworks
Work with R&D, CTO, and peer architects on system definition and trade-offs
Engage with customers and partners to shape system requirements and use cases