לוח משרות דרושים, לחיפוש זה נמצאו 34,872 משרות

Required Signal/Power Integrity Engineer, PhD Graduate
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:
Simulate high speed interface electrical behavior using HSPICE or other circuit simulators.
Generate precise electrical models (e.g., S-parameters, SPICE models) for components such as packages, PCBs, and connectors for use in simulations.
Collaborate extensively with cross-functional teams, including ASIC architects, digital/analog designers, physical design/layout engineers, and system engineers, to define specifications and resolve integration challenges.
Execute lab measurements utilizing test equipment like oscilloscopes, Vector Network Analyzers (VNA), Time Domain Reflectometers (TDR) , Spectrum analyzers to validate simulation outcomes and debug signal and power-related issues on silicon prototypes and boards.
Establish robust design rules and guidelines for optimal signal/power integrity during PCB and package layout, ensuring high production yield and reliability.

In this role, you will be responsible for building data infrastructure for performance tuning, and analysis of a new analytics product. As a member of our Data Performance team, you will collaborate closely with other SW & HW Engineers to improve the performance of our new cutting-edge APUs. You will collaborate with our business leaders and participate in the product design and implementation. You will evaluate, implement, and integrate a diverse set of tools and technologies such as Spark, Comet, Velox, Dagster, Hardware emulators and software simulators.





Join a multi-disciplinary team of experts operating at the foundation of data infrastructure stack

Build a robust data benchmarking infrastructure

Develop in-house measurements and ETL tools

Conduct detailed performance analysis and characterization

Research state-of-the-art benchmarks and techniques for SQL and data optimization

Were expanding a fast-growing practice that helps engineering teams leverage AI in their SW development lifecycle and transform into AI-native teams. Weve served dozens of satisfied customers in Israel and abroad and are now hiring a hands-on engineer to lead and drive R&D AI transformation programs, AI tooling adoption & tracking, create resources and run training at scale.
Key Responsibilities:
Own the AI R&D transformation and Agentic SDLC agenda across multiple clients: assessments, KPIs, rollout plans, training, champions programs, skills/agent developments, etc.
Lead AI Coding Tooling optimization end-to-end, plus evaluate/compare adjacent tools (e.g. Claude Code, Cursor, GitHub Copilot, Kiro, etc).
Create training materials (slides, exercises, demos) and deliver workshops; Train teams yourself and mentor trainer bench.
Develop AI infra & tooling, dashboards, frameworks, playbooks and AI resources (skills, agents, hooks, MCPs, etc) for clients to enable transformation, automation and governance
Partner with Sales/Delivery on pre-sales to attract new customers.
Stay on the cutting edge of releases and best practices, turn learnings into repeatable packages.

We are looking for an ATE Engineer to join our multidisciplinary team in central Israel.
The role involves developing and implementing complex automated test solutions, from requirements analysis through direct integration with hardware and Automated Test Equipment (ATE).
Key Responsibilities
Translate Test Requirements Documents (TRD) into automated Test Sequences/Scenarios using NI TestStand or OTM (ORION).
Develop, maintain, and enhance automated test sequences and deploy them in laboratory environments.
Integrate measurement instruments and communication protocols with ATE systems, perform debugging, and support troubleshooting activities.
Develop software components and DLLs in C# or C for hardware communication, when required.
Work closely with Hardware, Electronics, and Integration teams, including reading and interpreting electrical schematics.

Required Research Data Scientist II, Waze
About the job
The Personalized Experience team aims to give Waze drivers personalized, hyper-local, contextual and timely routing experience. The team contributes to the Personalized Navigation squad and more. The team members are embedded within the Waze development Squads. We develop and own Machine-Learning models from ideation to production, including research, production grade pipelines, feature engineering, experimentation, monitoring and dashboards, inspection and debugging.
The team works closely with the product team, helping to shape the requirements and success metrics. The team works closely with the Backend teams, integrating the models, ensuring a feedback loop to enrich the models, triage and solve users complaints, leading and guiding experimentation and more.
Waze is where people and technology meet to solve transportation challenges. It's a platform that empowers users to contribute road data and edit Waze maps to improve the way we move about the world. As the social navigation pioneer, Waze leverages mobile technology and a passionate global community to redefine expectations of todays maps.
Responsibilities
Feature engineering, model evaluation and error analysis, data processing and pipelines, model tuning, monitoring and dashboards.
Work with product managers, software developers and quality analysts to define requirements, formulate success metrics and lead experimentation.
Use data to help products to shape the future of Waze and drive innovation. Provide insights on user behavior and help engineers and quality analysts detect and solve complex problems.
Utilize Cloud Platform, Vertex AI, Python, Scikit-learn, TensorFlow, Airflow/Composer, Python and Looker tools.

Join the company and help scale AI capabilities across the organization. As the AI IT Centre of Excellence (COE) Deploy Lead, you will own the methodologies, standards, and deployment practices that make AI implementation repeatable and reliable across Strauss.
You will act as the professional focal point for AI delivery - working alongside AI experts, data teams, software developers, architects, and business stakeholders to ensure consistent, high-quality delivery of AI initiatives while building organizational knowledge and capability.
Employment model: Israel-based, offshore/outsourcing engagement (not a buy-out).
Key Responsibilities
Lead the deployment methodology, standards, and best practices of the AI IT Centre of Excellence (COE).
Guide and support development teams in the design, implementation, and adoption of AI solutions.
Serve as the professional focal point for AI delivery frameworks, tools, architectures, and implementation approaches across the organization.
Facilitate collaboration between AI experts, data teams, software development teams, architects, and technology stakeholders.
Provide training, coaching, and ongoing enablement for teams delivering AI initiatives.
Build and maintain AI playbooks, implementation guidelines, reference architectures, templates, and knowledge assets.
Drive consistency, quality, governance, and scalability across AI implementations.
Support project execution, manage dependencies, identify risks, and help teams overcome implementation challenges.
Lead AI knowledge-sharing activities, communities of practice, and professional development programs.

We are looking for an Analytics Engineer (contract) to join Artifactory Product Analytics and build the data platform behind how we measure our products. You will own the engineering side of analytics: designing product telemetry with PMs and R&D, modeling that data into trusted, reusable datasets in the warehouse, and making those datasets easy for analysts and stakeholders to consume. Product analysts own the product questions and metric definitions; you make the data underneath them fast, consistent, and dependable.
You will work inside an AI-native analytics environment (Cursor, Claude, and similar coding agents) as the default way of shipping - not as an optional add-on.
Fixed-term contract: 6-8 months. Start date: October 12, 2026.
Responsibilities:
Design telemetry: partner with PMs and R&D to define event and data specs for product usage - schemas, properties, validation, and the path into the warehouse (core, ongoing part of the role)
Build the modeled layer: develop and maintain dbt transformation models (staging → intermediate → gold) so Artifactory product data is consistent, tested, documented, and reusable
Enable self-serve: with the analysts, design and implement how stakeholders reach certified product data so recurring questions don't need a custom pull
Align definitions: standardize entities, grain, and model structure across Artifactory areas together with the analysts who own product meaning
Ship in an AI-native workflow: specs, SQL, dbt models, reviews, and documentation done in Cursor / Claude and equivalent tools.

We are looking for an Analytics Data Engineer (contract) to join Artifactory Product Analytics and build the data platform behind how we measure our products. You will own the engineering side of analytics: designing product telemetry with PMs and R&D, modeling that data into trusted, reusable datasets in the warehouse, and making those datasets easy for analysts and stakeholders to consume. Product analysts own the product questions and metric definitions; you make the data underneath them fast, consistent, and dependable.
You will work inside an AI-native analytics environment (Cursor, Claude, and similar coding agents) as the default way of shipping - not as an optional add-on.
Fixed-term contract: 6-8 months. Start date: October 12, 2026.
Responsibilities:
Design telemetry: partner with PMs and R&D to define event and data specs for product usage - schemas, properties, validation, and the path into the warehouse (core, ongoing part of the role)
Build the modeled layer: develop and maintain dbt transformation models (staging → intermediate → gold) so Artifactory product data is consistent, tested, documented, and reusable
Enable self-serve: with the analysts, design and implement how stakeholders reach certified product data so recurring questions don't need a custom pull
Align definitions: standardize entities, grain, and model structure across Artifactory areas together with the analysts who own product meaning
Ship in an AI-native workflow: specs, SQL, dbt models, reviews, and documentation done in Cursor / Claude and equivalent tools.

Required Networking Silicon Architect, 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 part of the team, you will define solutions for high-performance network accelerators and interconnects in data centers. You will have dynamic, multi-faceted responsibilities in areas such as project definition, with close collaborations with data center systems and Software teams. You will participate in the design, architecture, documentation, and implementation of the next generation of data center networking infrastructure.
You will be responsible for performance analysis for an end-to-end networking stack using your deep knowledge of high speed network infrastructure.
We're behind groundbreaking innovations, empowering the development of AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Cloud, Global Networking, Data Center operations, systems research, and much more.
Responsibilities
Evaluate different silicon solutions for executing our data center networking roadmap, off-the-shelf components, vendor co-developments, custom designs, and advanced silicon integration technologies.
Design high-performance hardware/software interfaces.
Collaborate closely with system, software, verification, emulation, physical design, packaging, and silicon validation stakeholders to ensure that designs are complete, correct, and performant.
Drive vendor execution in various engagements: standard component roadmaps, build to specification, and co-developments.
Contribute to the evaluation of future ASIC designs and general architecture.

We are looking for a hands-on Backend Engineer to join an innovative R&D team building a cloud-native product. You will deliver high-quality Go (and Java where needed) using modern cloud frameworks, and own features end-to-end - from design through production health.
Responsibilities:
Design, implement, and ship backend services for a cloud-native product - from design through production
Write clean, testable, maintainable Go (and Java where needed)
Own features end-to-end with your team: APIs, data model, tests, rollout, and production health
Partner with product and peers on design trade-offs for scalability and reliability
Proactively propose and drive incremental product improvements, not just ticket work
Keep pace with DevOps and cloud-native practices that affect how we build and run software.

We are looking for a highly skilled Senior Data Platform Engineer to join our Data Platform team and play a key role in designing, building, and evolving the companys data infrastructure.

This is a hands-on engineering position focused on developing scalable data platforms, high-volume ingestion pipelines, and the foundational data systems that power analytics, product applications, AI workloads, and large-scale model execution. You will help architect our data lake, build reliable ingestion capabilities at scale, and shape the core infrastructure that supports the companys future growth.

This is an exciting opportunity to work with cutting-edge technologies and have a defining impact on the architecture and evolution of our data platform.


What Youll Do
Build complex, high-volume batch and near-real-time ingestion services while helping evolve the platforms streaming capabilities.
Design and implement data solutions for all application requirements in a distributed microservices environment
Develop and optimize large-scale data pipelines for batch and streaming use cases.
Ensure data quality, compliance, and governance.
Manage and optimize Kubernetes infrastructure, utilizing KEDA to dynamically scale resources for large-scale data processing workloads.
Own the full lifecycle of our data stack using Terraform and Kubernetes, from provisioning to application-level frameworks.
Provide technical guidance for the team, drive best practices around infrastructure, CI/CD, testing, and system design.
Deep-dive into memory management and performance tuning to ensure our large-scale distributed systems are both cost-effective and lightning-fast.

The company is a leading direct-to-consumer platform for app publishers, processing more than $1B annually. As a Senior Backend Engineer you will build and evolve core backend systems - high-scale, cloud-native services that power critical business flows - with end-to-end ownership from design and architecture to production, monitoring, and continuous improvement.
Responsibilities:
Design and maintain scalable, high-availability backend services in cloud-native environments.
Own features end-to-end: design, implementation, deployment, monitoring, and optimization.
Contribute to system architecture, API design, data modeling, and event-driven flows.
Write maintainable code and participate in design/code reviews.
Optimize performance, reliability, and resource usage.
Collaborate with Product on translating business requirements into technical solutions.
Mentor other engineers and improve engineering standards.