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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

We are seeking a detail-oriented, self-driven Security Analyst, based in Israel, to join the Risk and Compliance team and operate our ISO-aligned Event Management Process end-to-end. This role is the front door for security events in our company - the person who makes sure that every reported security event (from employees, vendors, and automated monitoring) is triaged, classified, escalated where required, and closed with documented evidence.

The Security Analyst is both an operator and a process owner. This is an excellent entry-point role for a Computer Science graduate or similar background person looking to build a foundation in security operations and compliance. You will run the daily flow of events, partner with Corporate IT, R&D/DevOps, and the CISO to drive down events, implement improvements and take corrective and preventive actions. You will report directly to the Chief Information Security Officer and work closely with the broader employee base engaging them directly.
This role covers five primary pillars: Security Event Intake and Triage; Classification, Escalation and Coordination; Process Operations and Continuous Improvement and Ai Automation.
This is a temporary position with an hourly pay.


RESPONSIBILITIES:
Event Intake & Triage
Own the front door for all reported security events - internal security hotline , IT services alerts, employee reports and automated monitoring - and make sure nothing falls through the cracks.
Triage security events within defined SLAs; gather context from logs, endpoints, identity systems, and SaaS admin telemetry to make a fast, defensible first call.
Maintain the Security Event Register as the single source of truth for every reported event - timeline, evidence, classification, owner, status, root cause, and corrective actions.
Review mail service admin holds that require review and investigation, user engagement and follow-up
Classification, Escalation & IRT Coordination
Classify security events against the defined severity matrix; distinguish security events from incidents and apply the agreed escalation criteria consistently.
Notify the CISO when escalation criteria are met, evidence collection, and timeline capture during incidents.
Process Operations & Continuous Improvement
Own and operate our ISO-aligned Event Management Process end-to-end - from intake through triage, response coordination, closure, and lessons learned.

This role has been designed as Hybrid with an expectation that you will work on average 2 days per week from our office.

Responsibilities:
Leads the project team for design and development of complex products and platforms, including solution design, analysis, coding, testing, and integration for building efficient, scalable and robust cloud subsystems.
Reviews and evaluates designs, test plans, and develops code for compliance with cloud design and development guidelines and standards.
Provides tangible feedback to improve product quality and mitigate risks.
Represents the engineering team in various technical forums and provides guidance and mentoring to less-experienced team members.
Drives innovation and integration of new technologies into projects and activities in the software systems design organization.
Analyzes science, engineering, business, and other data processing problems to develop and implement solutions to complex application problems, system administration issues, or network concerns.

We are looking for a Senior Data Engineer responsible for designing, building, and maintaining the infrastructure necessary for analyzing large data sets. This individual should be an expert in data management, ETL (extract, transform, load) processes, and data warehousing and should have experience working with various big data technologies, such as Hadoop, Spark, and NoSQL databases. In addition to technical skills, a Senior Data Engineer should have strong communication and collaboration abilities, as they will be working closely with other members of the data and analytics team, as well as other stakeholders, to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with the overall business goals and objectives.

What You'll Do
Work closely with data scientists/analytics and other stakeholders to identify and prioritize data engineering projects and to ensure that the data infrastructure is aligned with business goals and objectives
Design, build and maintain optimal data pipeline architecture for extraction, transformation, and loading of data from a wide variety of data sources, including external APIs, data streams, and data stores.
Continuously monitor and optimize the performance and reliability of the data infrastructure, and identify and implement solutions to improve scalability, efficiency, and security
Stay up-to-date with the latest trends and developments in the field of data engineering, and leverage this knowledge to identify opportunities for improvement and innovation within the organization
Solve challenging problems in a fast-paced and evolving environment while maintaining uncompromising quality.
Implement data privacy and security requirements to ensure solutions comply with security standards and frameworks.
Enhance the team's dev-ops capabilities.

We are looking for a Senior AI Researcher to join Immunais foundation models team and help advance large-scale models for single-cell RNA (scRNA) data.

In this role, you will focus on training and improving transformer-based and deep learning models, developing algorithmic solutions to challenging modeling problems, and adapting modern foundation model techniques to biological data. This is a hands-on research position for someone who enjoys building and training deep models, understanding their behavior, and pushing them to perform better.

You do not need prior biology experience - but you should be excited to apply your deep learning expertise to a new scientific domain.

Location: Ramat Gan (hybrid model).

What will you do?
Develop, train, and refine transformer-based and related architectures for large-scale scRNA data.
Tackle challenging modeling problems with thoughtful, principled approaches.
Apply ideas from NLP and vision (pretraining, self-supervision, transfer learning) to biological data.
Plan careful experiments, perform ablations, and deeply analyze results to guide model improvements.
Engage directly with large, noisy biological datasets and build intuition for model behavior in this setting.
Partner with engineers, data scientists, and biology experts to turn research ideas into working systems.