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The Cellular group is seeking a highly skilled Software Engineer to join our team and develop cutting-edge Automation Infrastructure for DevOps and beyond.

In this role, you will contribute to engineering efforts from design to implementation, solving complex technical challenges in multiple areas focusing on CI/CD & SW tool development.

Responsibilities
In this pivotal role, your responsibilities will include:
Design, implement, and maintain CI/CD pipelines for seamless software deployment.
SW Tools development - from idea, requirements definition, the tool's design to its implementation.
Set up infrastructure processes and methodologies to increase the groups efficiency.
Automatic deployment: control and optimize configuration management (with tools such as Ansible, Puppet, or Chef).
Proven database experience.
Monitor system performance, reliability, and scalability.
Troubleshoot infrastructure and deployment issues, ensuring high availability.
Take part in the optimisation & development of our data path solution.
Working on a varied set of platforms/technologies.

As an Embedded Software and Prototyping Engineer working on visionOS platforms, you will be responsible for designing, prototyping, and developing real-time software across the visionOS stack.

Responsibilities
Define, design and develop software solutions for our AR/VR technology.
Work cross-functionally with multiple teams, drive requirements, and deliver end-to-end solutions.
Understand the end customer use-cases, and design and develop software solutions tailored to those experiences.
Develop early prototyping software solutions in simulation/emulation environment.
Deliver shipping quality software solutions.
Identify and implement efficient system-level solutions across HW and SW to meet the product's performance goals within the power constraints.
Debug hard to reproduce issues and propose solutions with minimum impact to user experience.

Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.

We are looking for a Backend Engineer to join our MLOps team and help build the infrastructure that powers cutting-edge AI models.
In this role, youll manage the end-to-end MLOps lifecycle, designing event-driven systems that handle massive video data and moving compute-intensive, generative models from research to production.
You'll collaborate closely with AI researchers and video-processing teams to ensure our AI services are scalable, reliable, and performant.

Were hiring a Mid-Level DevOps Engineer to join our growing infrastructure team. You'll be working hands-on with modern AWS-native technologies, helping us scale secure and observable cloud environments, while partnering closely with developers to build and ship reliably.
Responsibilities:
Manage scalable, production-grade AWS infrastructure with Terraform
Maintain Kubernetes clusters, including deployments, autoscaling, and ingress
Handle cross-service communication using Kafka, SQS, or PubSub
Set up observability and alerting using Grafana, Prometheus, and log aggregation tools
Integrate Cloudflare for traffic protection, rate limiting, and caching
Manage and improve CI/CD workflows using GitHub Actions and ArgoCD
Collaborate directly with developers on environment setup, debug sessions, and deployments
Implement IaC and GitOps patterns across services and teams

Required Software Engineer III, Data and AI Infrastructures, Waze
Tel Aviv, Israel
About the job
Our software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. 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 needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. 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.
The team manages all engineering infrastructure for Waze data scientists, including: GenAI frameworks for internal applications and analytics (DataWhiz), evaluation frameworks for user-facing features, and MLOps for training and deploying ML models at scale. Additionally, the team oversees data pipeline infrastructures, infrastructure as code, and the application of engineering best practices within data science.
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
Add new features to our GenAI analytics agents serving all of Waze for any data analytics questions.
Research in GenAI for ML research and exploration, backend GenAI models evaluation framework.
Understand ML or Data Science to have knowledge of the users of the framework.

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

Required Software Engineer III, Hoverboard
Responsibilities
Write product or system development code.
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).
Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.

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

We Are KPMG Israel KPMG Israel is more than a professional services firm, we are a community of people driven by impact. As part of a leading global network, we partner with the most influential organizations to drive large-scale business and technology transformation, combining strategic thinking, innovation, and advanced technologies. Guided by integrity, excellence, and forward thinking, we help organizations navigate complexity and create real change. Our people are at the center, with space to lead, experiment, and grow in a dynamic and collaborative environment that connects personal development with meaningful impact on the future of business and society We are seeking a skilled and motivated Elastic Platform Engineer to join us. As Elastic Platform Engineer, you will be responsible for the design, implementation, operation, and ongoing maintenance of Elastic stack environments. Role Responsibilities
* Ongoing operation and maintenance of enterprise Elastic environments.
* Monitoring, alerting, and system management.
* Integration with other cloud and platform services.
* Load and performance testing.
* Design and implementation of Kafka-based ingestion pipelines into Elastic.
* Continuous improvement, stabilization, and optimization of the Elastic platform.

Flytrex is building an autonomous drone-delivery network for restaurants in suburban America. We are one of 4 companies that are FAA approved to fly over residential neighborhoods (together with Amazon, Google/Wing and Zipline) but are the only one exclusively focused on restaurants. Uber is an investor in Flytrex and we fly deliveries for Doordash as well. After thousands of successful commercial deliveries and multiple breakthrough FAA approvals, Flytrex is now expanding rapidly across the U.S., starting with Dallas-Fort Worth. Flytrex is revolutionizing the food delivery field by making drone delivery a reality and We’re looking for an Experienced Software Developer to join a team that develops the core technology that powers our drones . The position is meant for individuals who can handle complex logic and have some familiarity with embedded software. This is a unique opportunity to develop the world’s leading drone delivery service and be a part of a revolution in the making.

We're looking for a passionate and detail-oriented QA Engineer (Entry Level) to join our quality assurance team.

This is your chance to enter the high-tech world and grow within a supportive, innovative environment.

What You'll Do:
Design and execute manual test cases for our products - get hands-on experience with real systems and ensure product quality from the ground up.
Collaborate closely with developers, product managers, and UX designers to detect bugs and improve the user experience.
Learn and apply professional QA methodologies - including writing test scenarios, working with QA tools, and understanding real-world product behavior.
Grow gradually into automation testing, performance testing, or other technical tracks, based on your skills and interests.

We are a hyper-growth company, and our development team is hiring talented and experienced Backend Engineers to design and develop end-to-end major features and new services.

Responsibilities
Work closely with the founding team and product managers.
Support the availability of our service, participate in the on-call shifts.
Innovate, Lear, and Teach.

We are looking for an experienced Backend Engineer (4+ years) to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development program.

In this role, you will act as an AI Champion and Technical Mentor within the clients R&D organization. Your mission is to help development teams effectively integrate AI tools, agentic coding workflows, and best practices into their daily software development lifecycle (SDLC). You will help guide teams through AI adoption, help overcome resistance, and ensure AI delivers real value.

This is not a feature-delivery or coding-focused role, especially in the early stages, the position is centered on enablement, training, and integration, working closely with teams to embed AI development tools into real workflows and support the organizations AI transformation.

This is a high-impact role focused on technical enablement, AI expertise, and effective collaboration with development teams and intended for experienced engineers who actively use AI in their day-to-day development work and are looking to influence how teams work. Success in this role looks like teams shipping faster and smarter with AI, not lines of code written.



What Youll Do:

● Help drive adoption and optimization of GitHub Copilot and AI dev tools

● Support (mostly) backend engineers, answer technical questions and help unblock teams

● Continuously track the AI tooling landscape and best practices

● Measure impact, identify gaps and improvement opportunities across the SDLC

● Navigate and reduce change resistance to change with patience and empathy

● Partner with DevOps, architects, and management to track and optimize AI utilization

● Build and maintain a library of reusable AI assets (prompts, rules, agent workflows, playbooks) tailored to the clients stack

● Serve as the go-to escalation point for GitHub Copilot-related issues, edge cases, and feature rollouts

We are looking for a Software Engineer (4+ years) with experience working with COBOL/Mainframe to join the team as an AI Integration Engineer, supporting one of our enterprise clients as part of their AI-Native Development initiative.

In this role, youll act as an AI Champion and Modernization Leader, working closely with development teams maintaining and evolving mainframe applications. Your mission is to help these teams integrate AI tools, agentic coding workflows, and emerging AI development best practices into their legacy and hybrid SDLC environments.

The focus is on enablement, training, and integration - not direct feature delivery. Youll bridge the gap between traditional mainframe development and AI-assisted software engineering, empowering teams to leverage tools like GitHub Copilot and emerging large-language-model (LLM) capabilities to accelerate modernization and improve developer experience.

This is a high-impact, high-visibility position designed for engineers who are hands-on with AI tools and want to influence how enterprise teams evolve their engineering practices. Success in this role looks like legacy teams delivering faster and smarter with AI - not lines of COBOL code written.

What Youll Do:

● Drive adoption and optimization of GitHub Copilot and other AI development tools in a variety of environments, including COBOL/Mainframe

● Mentor and support mainframe and backend engineers; answer questions, demonstrate workflows, and unblock teams

● Identify opportunities to use AI for code understanding, refactoring, documentation, and modernization

● Continuously track the evolving AI tooling landscape, surfacing relevant capabilities for mainframe use cases

● Measure impact, collect feedback, and identify improvement opportunities across the modernization lifecycle

● Navigate resistance to change with patience and empathy while promoting a learning culture

● Build a library of reusable AI assets (prompts, scripts, workflows) tailored to mainframe and integration contexts

● Partner with DevOps, architects, and management to track adoption and optimize AI utilization across projects

● Serve as the internal expert for GitHub Copilot and related AI dev tools, piloting new features, and best practices