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The MLIL FLOW team is looking for a Senior Software Development Engineer to lead the design and delivery of systems software for our next-generation ML accelerator servers. We build production software to validate, initialize, monitor, and qualify these servers - from first silicon through fleet-scale deployment. We work on the physical systems that execute ML workloads: Server bring-up, hardware diagnostics, interconnect validation, power/thermal monitoring, and fleet-scale operations are our bread and butter.


Key job responsibilities
Lead the architecture and implementation of hardware validation and diagnostic software for new ML acceleration platforms.
Drive technical direction for PCIe validation, power/thermal diagnostics, and stress-testing frameworks that run across manufacturing, vetting, and production environments.
Own subsystems end-to-end: from design through implementation, testing, deployment, and operational excellence at fleet scale.
Work with Hardware, Manufacturing, EC2 teams to create coordinated software packages that enable both qualification and rapid deployment.
Debug and root-cause complex hardware/software interaction failures on first silicon and production fleet returns; drive root-cause to closure.
Build and maintain data pipelines, dashboards, and monitoring systems for fleet health and performance benchmarking.
Mentor engineers, define best practices, drive design reviews, and raise the bar for the team.
Lead multiple development initiatives in parallel, balancing schedule, risk, and technical quality across a fast-moving hardware program.

We are seeking an Applied Scientist to help build our next-generation customer memory and personalization systems.

As an Applied Scientist, you will design and build ML and LLM-powered solutions for our customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems.

You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences.
You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage.
You will collaborate closely with engineering and product teams to translate research into measurable customer impact.

We are seeking an Applied Scientist to help build our next-generation customer memory and personalization systems.

As an Applied Scientist, you will design and build ML and LLM-powered solutions for our customer memory and personalization systems. You will work on how customer knowledge is extracted, validated, and applied in production systems.

You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will deliver high-quality, scalable systems that power customer-facing experiences.
You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage.
You will collaborate closely with engineering and product teams to translate research into measurable customer impact.

We are looking for talented engineers to help us develop a semiconductor platform based on a revolutionary architecture.

The Data Path HAL team is looking for an Embedded Software Engineer (Junior), to join us in building the next generation of networking products. Youll have the opportunity to work on the technologies that power the worlds largest cloud provider, in a dynamic, open, fast-paced environment.
Working in both pre-silicon and post-silicon activities defines the Data Path HAL team as a leading team in AWS software development.

In this role you will be leading tasks involving peers from multiple disciplines, while enjoying every step of the journey.
You will have the opportunity to work on the heart of the network engine, at the worlds largest cloud provider, in a dynamic, open, fast-paced environment.

We are seeking an Applied Science Manager to lead a team building our next-generation customer memory and personalization systems.

As an Applied Science Manager, you will lead a team of scientists working on LLM-powered memory and personalization systems. You will define the scientific direction for how customer knowledge is extracted, validated, and applied in production systems.

You will own the end-to-end delivery of ML solutions, from problem formulation and modeling to offline and online experimentation, and production deployment at scale. You will ensure your team delivers high-quality, scalable systems that power customer-facing experiences.
You will drive work across areas such as fact extraction, memory quality and lifecycle, temporal reasoning, and grounded personalization, while navigating tradeoffs between quality, latency, and coverage.
You will hire and develop scientists, raise the scientific bar, and foster a culture of ownership and rigor. You will partner closely with engineering and product teams to translate research into measurable customer impact, and represent your teams work to senior leadership.

We are looking for a System Software Development Engineer to help define, shape, and integrate innovative solutions for the next generation of our cloud platforms.
In this role, you will be part of the System Software team, responsible for building and maintaining the software systems that validate servers before they enter our production. You will design and develop scalable test infrastructure, work closely with hardware and embedded components, and play a key role in ensuring the quality and reliability of our systems at scale.

You will collaborate with cross-functional teams, including hardware, firmware, and manufacturing, to gather requirements and deliver robust solutions. The role involves hands-on development in a Linux-based environment, deep system-level debugging, and full ownership across the software development lifecycle- from design and implementation to deployment in manufacturing environments.

This is a unique opportunity to work at the intersection of software and hardware, influence large-scale production systems, and contribute directly to the reliability of our infrastructure worldwide.

Key job responsibilities
We are seeking a new member to join the System Software team and contribute to a variety of projects and related activities:
- Work in a Linux-based environment.
- Build and maintain the software system that validates every server entering our production line.
- Design and develop framework infrastructure for executing hardware tests.
- Collaborate closely with internal and external customers to gather requirements and deliver solutions.
- Participate in the full software development life cycle, from design to manufacturing.
- Work hands-on with hardware interfaces and embedded systems to develop, validate, and debug system functionality.

In this role you will develop system level software, targeting chip architecture, functional correctness and performance, running on various platforms and validating chip functionality.

We're looking for exceptional engineers to join our Pre-Silicon Verification team - the team that sits at the very center of the chip development lifecycle. Verification in our company isn't a downstream checkpoint - it's the connective tissue that spans the entire product journey:
It starts at product definition - we engage from day one, shaping requirements and translating product intent into verification strategies before a single line of RTL is written
It extends into software - we work side-by-side with SW teams, verifying hardware-software interfaces and ensuring seamless integration across the stack
It reaches into physical design - we verify physical design aspects within functional verification, bridging the gap between logical correctness and silicon reality
It closes the loop - from spec to silicon, our verification touches every team and every stage of chip development
What sets us apart:
Agentic AI is embedded in our workflow - not as an experiment, but as a core part of how we design and verify chips.
Cutting-edge methodologies drive every stage of our verification process
Relentless innovation - we don't settle; we actively seek new approaches that raise the bar on silicon quality.
We do classic functional verification(SV/UVM/TLM), but beyond that, we touch physical design aspects, to ensure that the quality of our silicon is beyond logical functionality.
Performance optimization at all levels it is at the heart of our targets on top of logical correctness verification.
If you want to be at the nerve center of chip development - where your work connects every discipline and powers the backbone of AWS Graviton - this is your team.

We are seeking a CAD LEQ (Logical Equivalence Checking) Engineer to develop, deploy, and support equivalence checking methodologies across complex SoC programs. This role focuses on ensuring functional correctness between RTL, synthesized netlists, and post-implementation designs, while driving scalable, robust sign-off flows.

Responsibilities
Own and maintain LEQ sign-off methodology across RTL-to-GDS flows.
Develop and support flows using tools such as Cadence Conformal and equivalent industry solutions.
Drive power-aware equivalence checking including CPX flows.
Enable ECO flows, ensuring safe and correct implementation of late-stage design changes.
Debug equivalence failures and perform root-cause analysis across RTL, synthesis, and PnR stages.
Collaborate with design, synthesis, PD, and power teams to resolve mismatches and improve convergence.
Optimize runtime, capacity, and scalability of LEQ flows for large SoCs.
Define best practices, guidelines, and automation for LEQ usage across projects.
Partner with EDA vendors to resolve tool issues and drive feature improvements.

Join a highly skilled engineering team building core storage infrastructure across multiple system layers. You'll develop and enhance frameworks that handle disk image operations, provide unified storage abstractions, and enable cutting-edge virtualization technologies. This role requires both breadth and depth, comfortable working from kernel-level drivers to user-space frameworks, debugging complex multi-layered systems, and collaborating across hardware, kernel, and application teams. You'll participate in all phases of development: architecture, implementation, optimization, testing, and integration with deeply integrated platform features.

Responsibilities:
Develop kernel-level storage components and user-space frameworks for macOS and our other platforms.
Optimize I/O performance, resource utilization, and power efficiency across the storage stack.
Debug and resolve complex issues spanning hardware, firmware, kernel, and user-space boundaries.
Collaborate with cross-functional teams, including hardware, kernel, filesystem, and virtualization engineers.
Write comprehensive test suites, performance benchmarks, and technical documentation.
Contribute to architecture decisions and long-term technical direction for storage systems.

A hands-on engineering role focused on building production-grade AI/ML systems and the automation infrastructure that supports them - driving AI adoption into developer workflows, internal tooling, and domain-specific applications across the organization.

As a member of the AI Infrastructure & Applications team, you will lead the design, development, and production deployment of AI/ML-powered systems alongside the automation infrastructure and developer platforms that support them.
You will architect intelligent, scalable solutions used across the organization - driving AI adoption into developer and automation workflows, internal tooling, and domain-specific applications - while also building and maintaining the automation frameworks and infrastructure those systems depend on.
The systems you build are expected to be production-grade, reliable, observable, and continuously improving.

Responsibilities
Architect and ship end-to-end AI-powered applications and pipelines, from prototype to production.
Build agentic systems, RAG pipelines, and tool-use patterns that integrate LLMs into real workflows.
Define and own AI quality metrics (accuracy, groundedness, hallucination rate, task completion) and integrate them into CI/CD release gates.
Design evaluation frameworks for non-deterministic systems: offline evals, human-in-the-loop review, and automated regression suites.
Harness AI/LLMs to extend and enhance existing automation infrastructure, improving system performance and operational efficiency.
Build scalable automation frameworks, APIs, and tooling used across the organization.
Collaborate with engineering, CI, and domain teams to address automation needs across hardware, software, and cloud.
Distill requirements from a large, diverse user base into generic, reusable, maintainable solutions.
Implement monitoring, drift detection, and structured feedback pipelines for continuous improvement.
Apply rigorous engineering discipline - test design, release criteria, rollback strategies - to AI-native deployments.
Partner with product, design, and domain experts to define use cases, acceptance criteria, and rollout plans.

Develop and maintain internal EDA tools and frameworks for RTL assembly and connectivity checking.
Implement efficient algorithms for hierarchical RTL construction, module binding, and interface consistency across complex SoCs.
Build intelligent connectivity, visualization, and debug utilities.
Collaborate with front-end design, DFT, and integration teams to align methodologies and define tool requirements.
Drive automation and performance improvements, including runtime optimization and scalability across large designs.
Support adoption, documentation, and user training for internal design teams.

We are seeking a Machine Learning expert to join our wireless FW software group and explore innovative applications of ML algorithms in embedded wireless systems and protocols. This role focuses on cutting-edge research to integrate machine learning into wireless firmware architectures as well as protocol design, validation, and performance optimization. The position emphasizes experimental research, algorithm development, and proof-of-concept implementations in the wireless FW domain. This role offers the opportunity to develop novel solutions that bridge the gap between theoretical machine learning capabilities and practical wireless system implementations.
Responsibilities:
Research & Development: Design, develop, and evaluate machine learning algorithms optimized for real-time wireless communication systems operating under strict real-time, power and computational constraints.
Protocol Innovation: Create novel wireless protocols that intelligently incorporate ML techniques for enhanced performance, efficiency, and adaptability.
Algorithm Optimization: Adapt existing wireless algorithms (e.g. Link Quality, QoS, Scheduling etc) by integrating ML approaches while maintaining real-time performance requirements.
Data Collection & Analysis: Gather, analyze, and curate statistics from existing wireless devices and networks to enable ML model training and validation. Design and implement data collection frameworks for various wireless environments and use cases.
System Integration: Develop lightweight ML models suitable for deployment on resource-constrained wireless devices, including edge computing scenarios.
Performance Analysis: Conduct comprehensive performance evaluations through simulation, theoretical analysis, and experimental validation.
Research Publication: Publish findings in top-tier conferences and journals, and present research at industry conferences.
Collaboration: Work closely with hardware engineers, system architects, and product teams to ensure research translates into practical solutions.
Technology Scouting: Stay current with emerging trends in ML, wireless communications, and edge computing technologies.

As a Wireless Firmware Architect you will focus on defining technical direction, conducting research and analysis, and providing architectural guidance for our Bluetooth embedded solutions.

The position emphasizes wireless protocol design and simulations, software architecture definition, technical planning, proof-of-concept development and performance optimizations.

Responsibilities:
Define comprehensive software architecture for our Bluetooth embedded solutions.
Establish firmware architectural guidelines and principles.
Support development teams with architectural guidance and consultation.
Integrate performance and power analysis requirements into architectural frameworks.
Create technical demonstrations to support architectural decision-making.
Monitor and analyze hardware implementations to ensure alignment with software architectural requirements.
Evaluate hardware design decisions and their impact on firmware architecture.
Collaborate with hardware teams to provide architectural input and recommendations.
Design and develop proof of concept (PoC) projects to validate architectural approaches.
Research and prototype emerging wireless technologies and methodologies.
Evaluate feasibility of new technologies and integration approaches.
Design and develop wireless protocol simulation frameworks, develop intelligent simulation environments for protocol validation and optimization.
Analyze new standards and specifications for architectural implications.
Track industry trends and emerging wireless technologies.

We are a global leader in high-performance smart energy technology, with over 3000 employees, offices in 34 countries, and millions of products installed in over 133 countries. Our diverse product offering comprises intelligent solar inverters, battery Storage, backup systems, EV charging, and complete home energy management ecosystems. By leveraging world-class engineering capabilities and with a relentless focus on innovation, we strive to create a world where clean, green energy from the sun is the primary source of power for our homes, businesses, and just about everywhere we thrive
The IoE group specializes in making our devices smarter and more connected. What You Will Be Doing:
* Develop and design high-quality code following best practices to ensure reliability, maintainability, and scalability.
* Optimize and enhance the performance of existing software components.
* Collaborate with hardware engineers to ensure seamless integration between hardware and software.
* Lead technical discussions, code reviews, and mentor junior engineers.
* Participate in the full software development life cycle including concept, design, development, deployment, and support.
* Leverage cutting-edge AI tools and the latest development features to accelerate development, improve code quality, and drive innovation across the team.
* On the Interface team, you'll develop the core infrastructure handling all communication between the device and external systems - cloud, mobile, and other on-site controllers - deployed across millions of devices worldwide.


Country:
Israel

City:
Herzliya