לוח משרות דרושים, לחיפוש זה נמצאו 34,726 משרות

Required Silicon Validation and Debug Engineer
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
We prioritize security, efficiency, and reliability across everything we do - from developing our latest TPUs to running a global network, while driving towards shaping the future of hyperscale computing. Our global impact spans software and hardware, including Clouds Vertex AI, the leading AI platform for bringing Gemini models to enterprise customers.
Responsibilities
Contribute to developing and improving post-silicon test content that exercises both IP and SoC levels workloads and other compute-intensive scenarios.
Collaborate with architecture, design, and firmware teams to define comprehensive validation plans for SoC features, focusing on power consumption, thermal management, sensors behavior, and performance metrics.
Work closely with design and firmware teams to propose and implement solutions for optimizing SoC power efficiency and performance, including tuning core-to-memory latencies and bandwidth, power control loops, thermal control loops, etc.
Develop and maintain automated test scripts and frameworks (primarily in Python) to improve validation efficiency and coverage.
Participate in early silicon bring-up and platform bring-up activities, ensuring the stability and functionality of high-power multi-core SoCs.

Required SoC Test Engineer, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
Responsibilities
Collaborate with Architecture, Design and Verification teams to develop new product bring-up, validation, characterization, and qualification strategies and manufacturing test solutions for new High Performance Computing (HPC) products in advanced process technologies.
Verify test solutions on pre-silicon models (simulation or emulation) and develop ATE test modules and binning flows.
Develop and validate test programs on Automated Test Equipment (ATE) platforms for new product integration (NPI) in preparation for high volume manufacturing (HVM), working with ATE vendors and internal cross-functional teams.
Product sustain support, including volume data analysis, test time and yield improvements, assess test escapees and Return Merchandise Authorization (RMAs), localize failures, implement containment measures and partner with design, manufacturing, quality and reliability teams to root cause and implement corrective actions.
Develop tools, flows and methodologies to continuously improve and automate the testing life cycle.

Required Research Engineer, Generative Media, DeepMind
About the job
Our team's mission is to build frontier generative media experiences. We are pushing the boundaries of what is possible by developing real-time, interactive video models like Genie, as well as exciting new applications and capabilities.
We have a proven track record of researching and delivering foundational generative models for video and action-controllable virtual worlds, as well as applications such as video stylization, reference-to-video generation, and precise object insertion and removal.
Artificial intelligence will be one of humanitys most transformative inventions. At DeepMind, we are a pioneering AI lab with exceptional interdisciplinary teams focused on advancing AI development to solve complex global challenges and accelerate high-quality product innovation for billions of users. We use our technologies for widespread public benefit and scientific discovery, ensuring safety and ethics are always our highest priority.

We are pushing the boundaries across multiple domains. Our global teams offer diverse learning opportunities and varied career pathways for those driven to achieve exceptional results through collective effort.
Responsibilities
Design, implement, train, and evaluate novel deep learning models for real-time generative media, including video-audio synthesis, manipulation, and understanding.
Develop and optimize algorithms and systems for AI experiences on Omni platforms, focusing on live dialog, live video editing, and crosscut.
Collaborate with research scientists and engineers to prototype, experiment, and scale generative AI techniques using software engineering best practices.
Contribute to the design of datasets, evaluation methodologies, and infrastructure required for training and testing generative models.
Analyze results to iterate on architectures, contribute to research publications, and help deploy successful research into GDM and our products.

Required Design Verification Engineer, Networking, Cloud
About the job
Be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our direct-to-consumer products. You'll contribute to the innovation behind products loved by millions worldwide. Your expertise will shape the next generation of hardware experiences, delivering unparalleled performance, efficiency, and integration.
As a Design Verification Engineer, you will be a part of the Research and Development team to verify digital designs, develop constrained-random test environments and drive system testing to closure. You will collaborate with design and verification teams, manage the verification life-cycle and uncover bugs through corner-case testing.
Responsibilities
Plan and execute the verification of digital design blocks by understanding specifications and working with design engineers to define key verification scenarios.
Develop and refine random verification environments using SystemVerilog/Universal Verification Methodology (UVM) or Specman to ensure effective test coverage.
Define and implement various coverage measures to capture stimulus and corner-case scenarios.
Collaborate with design engineers to debug tests and ensure functional correctness of design blocks.
Drive coverage analysis to identify verification gaps and demonstrate progress towards tape-out.

we are pioneering the Autonomous Execution Layer for Cloud data & AI Workloads. Our platform dynamically orchestrates clusters, predicts workload bottlenecks, scales resources in real time, and auto-heals infrastructure anomalies for data -intensive & AI workloads -with zero human intervention. Operating in live production across global enterprise customers, our company delivers mission-critical resilience, sub-second optimization, and true zero-touch infrastructure Why Join Us Scale-Up Velocity, Core Team Ownership: Backed by top-tier VCs, scaling fast, and powering Fortune 500 & enterprise production environments, we combine scale-up stability with the architecture ownership, high-velocity iteration, and meaningful equity upside of an early-stage core engineering team. Elite Engineering Culture: Founded by veterans of elite IDF tech units and distributed systems leaders, we tackle deep infrastructure challenges in AI & cloud architecture. You will have full technical agency to shape what the company becomes from the ground up. Key Responsibilities
* Lead, design, and architect our production-grade enterprise web application and SaaS platform end-to-end
* Drive core system architecture and technology decisions, building scalable, low-latency APIs and intuitive frontend control planes.
* Build high-performance, Real-Time visual interfaces and explainability tools that allow enterprise engineering leaders to monitor and control autonomous cloud systems.
* Take complete end-to-end ownership across the entire lifecycle: from concept and design to implementation, testing, CI/CD deployment, and production monitoring.
* Collaborate closely with backend, AI, and distributed systems engineers to ship complex, mission-critical platform features.
What We Offer Top-of-Market Compensation: Highly competitive base salary benchmarking top-tier senior engineering talent in Israel. Significant Equity: Meaningful early-stage equity grants positioned above market standard. Pure Technical Impact: High agency, zero bureaucracy, and direct influence over the core product and architecture.
Ready to build the frontend and control plane for autonomous AI infrastructure? Hit Apply.

we are pioneering the Autonomous Execution Layer for Cloud data & AI Workloads. Our platform dynamically orchestrates clusters, predicts workload bottlenecks, scales resources in real time, and auto-heals infrastructure anomalies for data -intensive and agentic workloads -with zero human intervention. Operating in live production across global enterprise customers, our company delivers mission-critical resilience, sub-second optimization, and true zero-touch infrastructure
Why Join Us Scale-Up Velocity, Core Team Ownership: Backed by top-tier VCs, scaling fast, and running live in Fortune 500 & enterprise production environments, we combine scale-up stability with the high impact, rapid iteration, and meaningful equity upside of an elite core team. Deep Tech & AI-Native Culture: We solve the hardest cloud infrastructure and telemetry challenges. You wont just build dashboards-you will own production-grade data products and drive the core intelligence powering our autonomous engine.
Key Responsibilities
* Dive deep into massive enterprise-scale telemetry and workload datasets to uncover patterns, optimize cloud execution, and steer core product decisions.
* Design, build, and maintain production-grade data pipelines, analytics models, and internal platforms supporting Real-Time autonomous systems.
* Partner directly with engineering and leadership to translate complex multi-cloud performance metrics into actionable platform intelligence
* Develop robust data modeling frameworks, statistical analyses, and high-impact visual interfaces to measure system efficiency and model accuracy.
What We Offer Top-of-Market Compensation: Highly competitive base salary benchmarking top-tier startup talent. Significant Equity: Meaningful early-stage equity grants positioned above market standard. Pure Technical Impact: High agency, zero bureaucracy, and direct ownership over core data infrastructure.
Ready to shape the data engine behind autonomous AI workloads? Hit Apply.

We are looking for a Principal AI Security Researcher with deep, hands-on expertise in AI red teaming and AI security to lead and scale RLGyms AI security research efforts. This is not a traditional cybersecurity leadership role. We need someone who has directly worked on breaking, attacking, testing, and securing AI systems, particularly large language models (LLMs), generative AI applications, and agentic AI systems. The ideal candidate has significant practical experience designing and executing AI red-team programs, developing adversarial attacks, identifying AI-specific vulnerabilities, building automated red-teaming capabilities, and translating findings into effective guardrails and security protections. What you'll be doing:
* Lead and scale multidisciplinary teams focused on AI red teaming, adversarial testing, and AI security research.
* Design and execute sophisticated attacks against LLMs, GenAI applications, and agentic AI systems.
* Research attack techniques including prompt injection, jailbreaks, indirect prompt injection, tool abuse, agent manipulation, data leakage, model misuse, and adversarial behavior.
* Build and evolve AI red-teaming engines and automated adversarial testing systems, including RLGym.
* Building and scaling global AI security teams (red teaming, adversarial research, guardrails engineering) while fostering an innovation-driven security culture.
* Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems
* Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress- TEST models at scale.
* Partnering with product and engineering to design and deploy enterprise-ready AI guardrails - including policy enforcement layers, monitoring pipelines, and anomaly detection systems - and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).

About us:
we are widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Required Data Center Security Manager (English, Hebrew)
About the job
As a Data Center Security Manager, you deliver full pieces of a project and make significant contributions with minimal guidance. You use your knowledge of security technology, data analysis, and data visualization to plan efforts of a team responsible for small to medium sized initiatives by delivering value-added perspectives and influencing project direction. You contribute to cross-team collaborations, identify and recommend multiple creative ways to solve defined problems. You also demonstrate the behaviors expected of as captured in our cultural pillars, and you engage in community contributions to improve and sustain our culture and operations, making it a better place to work.
In this role, you will take ownership of key activities including security budgeting, and manage physical security vendor operations to ensure high-performance service delivery.
You will partner closely with cross-functional teams to implement security policies, lead investigations, and proactively mitigate operational risks. You will direct responses to active security incidents, coordinate critical event workflows, and serve as the primary, authoritative liaison with public safety officials and law enforcement.
Behind everything our users see online is the architecture built by the Technical Infrastructure team to keep it running. From developing and maintaining our data centers to building the next generation of our platforms, we make our product portfolio possible. We're proud to be our engineers' engineers and love voiding warranties by taking things apart so we can rebuild them. We keep our networks up and running, ensuring our users have the best and fastest experience possible.
Responsibilities
Implement established compliance processes aligned with Compliance, Strategy, and Risk Management (CSRM) policies, standards, guidelines, and relevant legal or regulatory requirements.
Manage the security related costs through budget, forecasting, and invoice control for the assigned campus, assist management with financial analysis and input to financial decisions for security requirements.
Provide after-hours on-call management support and participate in emergent, large-scale event response or crisis management when needed.
Be responsible for the compliance, security and risk management program at the data center campus or related infrastructure which includes managing site security incidents, escalations, guard contract management and all other physical security related issues.

Required Machine Learning Hardware Architect, Hardware, Software Co-Design, Cloud
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Machine Learning Hardware Architect within the Co-design team, you will serve as a technical lead bridging model architecture innovation and next-generation hardware design. Operating at the highest levels of AI research and engineering, you will define the goal and architectural roadmap for our future machine learning serving and training capabilities. You will guide the integration of ML research such as massive-scale foundation models with advanced silicon architectures to create industry-leading, high-performance, and power-efficient accelerators.
Responsibilities
Define and drive the technical roadmap and architecture for the hardware/software stack to ensure exceptional performance for ML models. Act as the technical liaison across research, software, and hardware teams, steering model architecture innovation to maximize scaling, quality, and hardware efficiency.
Architect next-generation configurable simulation frameworks and performance models, setting the organizational standard for evaluating complex microarchitectural decisions. Drive high-stakes choices regarding Power, Performance, Area (PPA) and buildability for future chip and system architectures, expertly balancing long-term technological trends with strict product delivery timelines.
Guide system-level performance analysis across highly distributed ML systems, innovating new methodologies to optimize and balance compute, memory bandwidth, and inter-chip network requirements. Their leadership will directly shape the future of high-performance AI infrastructure and hardware-software co-design.
Manage cross-functional partnerships across hardware, compiler development and ML teams.

Required ChipDev CAD Engineer, Hardware, Cloud
About the job
Cloud's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to our Cloud's needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. You will anticipate our customer needs and be empowered to act like an owner, take action and innovate. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.
You will have the opportunity to find the perfect blend of software design practices and hardware development complexity. Whether your strength is in software coding, with a good understanding of hardware, or you are a hardware engineer with software proficiency, this balanced role will let you shine in both disciplines at the same time.
Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Manage project priorities, deadlines, and deliverables. Design, develop, test, deploy, maintain, and enhance software solutions.
Create software solutions that improve the hardware design process through automation. Propose, design, and implement software automation that directly addresses bottlenecks in today's ASIC and SoC EDA flow.
Work directly with the hardware team on projects prototype and then deploy tools to make a positive impact on our chip hardware development process. Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
Triage product or system issues and debug/track/resolve by analyzing the issues and the impact on hardware and quality.

Required Staff Embedded Firmware Engineer, High Speed DSP
About the job
In this role, youll work to shape the future of AI/ML hardware acceleration. You will have an opportunity to drive cutting-edge TPU (Tensor Processing Unit) technology that powers our most demanding AI/ML applications. Youll be part of a team that pushes boundaries, developing custom silicon solutions that power the future of our TPU. You'll contribute to the innovation behind products loved by millions worldwide, and leverage your design and verification expertise to verify complex digital designs, with a specific focus on TPU architecture and its integration within AI/ML-driven systems.
As a Staff Embedded Firmware Engineer for High-Speed DSP, you will architect and define the low-level firmware and control loops powering the world's most advanced physical-layer communications silicon. Sitting at the critical intersection of digital signal processing (DSP), hardware-software co-design, and real-time systems, you will lead the development of adaptive algorithms, error correction (FEC), and link-telemetry frameworks. Your work will directly bridge the gap between high-performance hardware pipelines and our planetary-scale AI infrastructure, transforming complex communication systems theory into reliable, real-time silicon execution.
Responsibilities
Define the long-term firmware roadmap and hardware-software partitioning for physical-layer interfaces, determining the optimal balance between hardware-fixed logic and programmable firmwarm.
Architect advanced "in-situ" monitoring systems and firmware-driven diagnostics to track physical-layer link health, Bit Error Rate (BER) trends, and channel quality across millions of ports in real-time.
Design, model, and implement bare-metal or RTOS firmware to control high-speed transceivers, managing real-time adaptive loops, clock and data recovery (CDR), and physical-layer calibration.
Partner with TPU Systems, Networking Software, and High-Performance Computing (HPC) teams to ensure silicon firmware integrates seamlessly with global cluster management and collective communication frameworks.
Identify and de-risk hardware-software interface bottlenecks (e.g., register maps, driver latencies, and boot-up sequencing) that impact our AI infrastructure.