לוח משרות דרושים בוגרי מדעי המחשב משרה מלאה, לחיפוש זה נמצאו 75 משרות

As part of our Wireless Connectivity group, you will be working on our latest products, both shipped and pre-released HW, developing tests to validate the PHY FW releases.
Youll be joining a dynamic and growing team of Firmware developers.
Youll work collaboratively with other engineering team members to develop and improve our coverage.
This positions primary focus will be creating scalable and robust test systems to support the delivery of new and existing features for a variety of our devices.

We are looking for a candidate who can take our tests and testing environment to the next level.
In this role, you will be working closely with the Wireless Connectivity Firmware engineers, providing a secure, high quality and robust regression supporting the development of firmware solutions. Targeted to increase the performance and stability of the different Wireless solutions.
You should have a strong background in tests and testing environment development, and a good knowledge and experience in Python.
Advanced problem solving and debugging skills should be a given.

As member of the DV CAD team, you have the opportunity to impact our engineers who develop next generation of our products!
You will be responsible for developing software solutions used by thousands of DV engineers globally. You will be supporting design process of all chip families we make (iPhone, iPad, Mac, our Watch and more), and your work will help streamline this complex process. This role combines DV knowledge alongside modern software engineering practices. Your work will be very diverse, and you will have broad impact contributing to the success of us.


You will develop and drive software development of multiple tools across the DV space, including cloud-native services, GUI, LLM harness, CI/CD. Your work will span from software development and architecture to collaborating with DV engineers, working with EDA vendors, and supporting critical project milestones.

Responsibilities
Developing and maintaining LLM harness for agentic DV workflows, and being responsible for benchmarking and improving accuracy of agentic workflows.
Building and managing cloud-native services running on k8s, including CI/CD, containerization, alerting, databases, GUI and monitoring.
Communication with DV stakeholders and working to understand user requirements.
Writing and maintaining Python scripts used as part of design simulation flows.
Supporting multiple projects simultaneously.

Our software team is growing, and we are looking for an SRE-DevOps Engineer to be entrusted with designing, building, and maintaining the infrastructure and automation frameworks that power our development ecosystem.

Your role will encompass end-to-end CI/CD pipeline ownership, cloud and on-premise infrastructure management, and ensuring the reliability, scalability, and security of our systems. You will be the backbone that enables our engineering teams to ship fast and confidently. We value agility, so staying updated and adaptable to our evolving tech stack is inherent to the role.

Responsibilities
Design, build, and maintain CI/CD pipelines to streamline development, testing, and deployment workflows.
Automate infrastructure provisioning, configuration management, and scaling operations.
Collaborate closely with development and data teams to understand and support their infrastructure needs.
Monitor system health, reliability, and performance, and drive incident response and resolution.
Enforce security best practices across infrastructure, access management, and deployments.
Manage and optimize containerized workloads and orchestration platforms.
Maintain and improve observability frameworks including logging, monitoring, and alerting.
Evaluate and integrate new tools and technologies to continuously improve the development infrastructure.

We are seeking a Head of Research to build and lead our research group reporting to the Co-founder and CTO. You'll set the research agenda for how AI agents, spanning coding agents, SaaS AI platforms, cloud, and endpoints, can be abused, and you'll turn that research into the detections and runtime protections that define our product. You'll build the team, the threat intelligence function, and the processes that keep us ahead of a threat landscape that changes weekly. This is a hands-on leadership role. You'll still go deep on platforms and attack paths while scaling research into a core differentiator of the company. You will help define the field of Agentic Security and be one of its leading voices.

Responsibilities

Lead and grow the research team: Hire, mentor, and manage AI security researchers. Build a culture of rigor, speed, and ownership.

Own the research direction: Proactively identify emerging agentic threats and platforms, prioritize research projects, and set a roadmap aligned with product and customer needs.

Build threat intelligence processes: Establish how we collects, triages, and operationalizes threat intelligence on agentic attacks. This includes in-the-wild abuse, malicious MCP servers, skills and extensions, and new techniques from the research community.

Drive research into product: Partner closely with engineering and product so findings become production detections, runtime policies, and governance capabilities. Own the coverage and quality of our detection logic.

Define detection strategy: Set standards for detection logic across environments, including coverage models, efficacy measurement, and false positive and false negative management at enterprise scale.

Stay hands-on: Lead deep dives into platform architectures, monitoring and enforcement boundaries, and end-to-end PoCs for the most critical attack paths.

Represent us externally: Publish research, advisories, and vulnerability disclosures. Speak at leading security conferences and build our reputation as the authority on agentic security.

Support customers and the field: Provide research expertise for customer engagements, incident investigations, and strategic accounts.

Develop the optimization and computational-geometry algorithms at the core of us: for researchers who love hard, non-convex problems.

As a Technical Project Manager at Jeen, you will lead the delivery of enterprise-grade AI projects from planning through execution. Youll work closely with customers, engineering, and cross-functional teams to ensure smooth technical integrations, clear communication, and on-time delivery. This role combines strong project management skills with a solid technical background, enabling you to translate complex requirements into successful, scalable AI solutions in a fast-growing, innovative environment.

Lead complex implementations, own client relationships, and drive innovation in fast-paced environments where your technical expertise creates real business impact.

Responsibilities
Lead and manage full-cycle implementation projects, from planning to go-live
Own the client relationship from a technical perspective- requirements, customizations, installations, and version updates.
Oversee the installation of JEENs platform across dev, test, and production environments, including integration with client systems.
Collaborate with IT stakeholders and internal engineering teams.
Coordinate cross-functional project roles in a matrix environment.
Create detailed project plans, track progress, and ensure on-time delivery.
Manage and execute version updates and technical change processes with the client.

As a Platform DevOps Engineer on the Core Platform, you will improve, operate, and scale our platform infrastructure. You will help accelerate development and deployment workflows while establishing strong standards for reliability, observability, performance, and security across enterprise AI products.

Key Responsibilities
Design, build, operate, and continuously improve cloud-native platform infrastructure and Development, Test, and Production environments.
Build, automate, and optimize CI/CD and deployment workflows using GitHub Actions, GitOps, and Argo CD.
Manage, maintain, and optimize Kubernetes environments, containerized workloads, Docker, and Helm.
Develop and maintain Infrastructure as Code using Terraform.
Partner closely with R&D teams to improve reliability, observability, performance, and security across the platform.
Establish and maintain monitoring, measurement, and alerting capabilities, including Prometheus-based tooling.
Develop automation and scripting tools that improve operational efficiency and developer experience.
Promote responsible and effective use of AI-powered code assistance and development practices.
Identify infrastructure bottlenecks and risks, and drive solutions that improve platform stability, scalability, and efficiency.

As a quantum researcher, your main role will be to develop algorithmic and error-reduction tools to help our partners and customers achieve quantum advantage for their applications. You will develop our error reduction methods, including mitigation and correction, and apply them to different use cases by optimizing existing methods, developing new algorithms, and adapting these tools to the realities of running on quantum hardware. This includes taking into account application requirements, noise characteristics, device constraints, and performance on real quantum devices.

Responsibilities
Developing new error reduction methods, including mitigation and correction, for quantum algorithms.
Optimizing error reduction methods for different algorithms, applications, and hardware settings.
Developing new quantum algorithms to enhance performance on real quantum hardware with error mitigation.
Conducting research on applications of quantum computing with our partners, including implementing and running proof-of-concept demonstrations of these applications on real quantum hardware. 

Landa is seeking an experienced Backend Software Engineer to join its R&D team. This hands-on role requires strong software engineering skills and the ability to develop complex, multidisciplinary systems that integrate backend software, image-processing algorithms, and advanced hardware. In this role, you will build backend software for real-time printed-output inspection, work with imaging algorithms to analyze print quality, and drive automatic corrections on high-speed digital printing presses.

Responsibilities:
· Design, develop, and maintain robust backend software and image-processing/inspection algorithms for a complex print quality inspection and control system, including defect detection, calibration, and related quality metrics. · Integrate software with industrial imaging hardware, including cameras/sensors, image-acquisition boards, timing/trigger systems, and motion control. · Troubleshoot and resolve complex software issues in development and production environments, including issues that span software, algorithms, and hardware. · Collaborate with cross-functional teams (software, algorithms, hardware, and process) to deliver innovative solutions. · Ensure high software quality through best practices, clean code principles, and testing. · Improve existing systems and drive modernization of legacy applications.

Attributes:
· Strong analytical and problem-solving skills. · High level of ownership and accountability. · Excellent teamwork and interpersonal communication skills.

Required Wafer-Scale System: Computation (LLM) and Communication (NoC) Co-Design
In this job opening, we are seeking a highly motivated and visionary researcher to join our team focused on chiplet-based computing systems. This role involves research and development in chiplet-based architectures, aiming to overcome performance and scalability limits of traditional compute platforms.
Responsibilities:
Conduct cutting-edge research on the co-design of communication and computation for wafer-scale systems. On the communication side, the work focuses on architecting Networks-on-Chip, providing scalable, high-bandwidth, and ultra-low-latency interconnects that efficiently span multiple dies and support fine-grained data movement. On the computation side, the research emphasizes optimizing and mapping training and inference workloads to fully exploit wafer-scale resources, improving performance, scalability, and energy efficiency through intelligent task placement and scheduling.
Investigate various aspects of system design, including:
Network-on-Chip design, further including Topology exploration, routing algorithms, and protocol/flow-control design to support high-throughput collective communication, low-latency synchronization, and efficient model/data parallelism
Expressing and Mapping LLM Parallelism to Wafer-Scale System that simplify LLM parallelism (e.g., tensor, pipeline, and data parallelism) and efficiently map training and inference workloads onto wafer-scale system.

We are looking for a highly analytical, detail-oriented Innovation Expert to join our Open Innovation team. This role is ideal for candidates who sit at the intersection of deep tech, startup ecosystem and academy, possessing strong technology analytical skills, clear communication, and a foundational background in computer architecture research.
In this role, you will drive our external innovation strategy by managing academic research collaborations, scouting early-stage deep-tech startups and conducting technical due diligence.
Key Responsibilities:
Academic Cooperation & Research Partnerships: Identify and build direct collaboration agreements with world-class professors, research labs, and universities. Facilitate joint research projects, tech-transfer initiatives, and track academic spin-offs.
Startup Scouting & Ecosystem Mapping: Actively identify, source, and map early-stage deep-tech startups and emerging tech companies globally within the companys strategic domains.
Technical Due Diligence: Evaluate startup technologies, product-market fit, and team capabilities. Analyze technical validity and assess how external innovations align with our internal roadmaps.
Ecosystem Analysis: Conduct deep-dive analyses of startup ecosystems, venture capital trends, and academic spin-offs to identify high-potential investment and collaboration opportunities.
Investment & Collaboration Support: Synthesize technical and commercial findings into clear, structured scouting reports, investment tech memos, and presentations for senior leadership to drive partnership or investment decisions.
Cross-Border Collaboration: Act as a bridge between startup founders, academic innovators, and internal global teams (including European and China-based business units) to facilitate joint POCs, or investment reviews.
Track Tech Domains: AI infrastructure, advanced semiconductors, hardware-software co-design, and AI data movement.

At Infinidat, a Lenovo company, we empower enterprises and service providers with cutting-edge storage platforms that redefine performance, reliability, and cyber resilience at scale. We're looking for an experienced Product Manager to assist with the strategy and roadmap for key areas of Infinidat's storage portfolio. At this role, you will work closely with R&D, customers, and go-to-market teams to translate enterprise requirements into product capabilities.

Responsibilities:

* Own the product roadmap and backlog for an assigned area of the InfiniBox/InfuzeOS portfolio.
* Gather and prioritize requirements from enterprise customers, Fortune 500 accounts, and field/sales teams, understand pain points and translate business needs into product and feature improvements.
* Write PRDs and detailed feature specifications for engineering, and confirm key requirements are met using hands-on validation.
* Partner with R&D on release planning, scoping, and prioritization trade-offs.
* Develop and maintain supporting documentation and best practices guides for the product area(s) owned, including deployment/configuration guidance, technical reference material, and internal enablement content for sales, support, and professional services.
* Support pre-sales, competitive positioning, and customer/analyst conversations.
* Track storage industry and market trends (AI/data workloads, cyber resilience, hybrid cloud, file and block) to inform strategy.
* Collaborate cross-functionally with marketing, sales engineering, professional services, and support organizations.

DealHub.AI is building the future of agentic revenue technology. Trusted by leading global businesses, we’re redefining what revenue teams can achieve with AI and agentic execution across the deal lifecycle. Our mission is simple: help businesses Own Your Revenue with greater speed, intelligence, and governance. As an Solution Expert you will serve as the technical trusted advisor for our customers, bridging AI capabilities with their specific business goals and revenue workflows You will embed deeply with customers. Part consultant, part engineer, part strategic advisor: leading AI sessions, configuring AI-driven workflows using DealHub MCP, training users on best practices, and ensuring measurable business outcomes. You'll collaborate closely with Customer Success, Product, Support, and Engineering teams, and will be the go-to expert for any AI-related technical solution. This is an ideal role for someone who thrives at the intersection of cutting-edge AI technology and real-world business challenges. This role is ideal for someone who thrives on ambiguity, moves fast, and finds equal satisfaction in writing clean code and presenting a solution to a CFO. Key Responsibilities
* Embed deeply with customers to understand their technical environment, business processes, and AI workflows and then design and build solutions that fit.
* Build and deploy AI-powered workflows, MCP-based automations, and intelligent features within the DealHub platform tailored to each customer's use case taking into account the integration landscape such as Salesforce, HubSpot, Dynamics, NetSuite, and billing platforms.
* Leverage LLM, AI, APIs, webhooks, data pipelines, automation scripts.
* Lead technical AI sessions — review requirements, demo solutions, help build agents and perform training.
* Translate complex AI and technical concepts into clear, tangible business value; operate as a trusted advisor, not just an implementer.
* Identify and resolve technical blockers proactively; operate with confidence under ambiguity and incomplete information.
* Build reusable engineering assets: integration libraries, prompt templates, and AI workflow scaffolding that scale across the customer base.
* Act as a direct feedback loop from the field to the Product and Engineering teams surfacing patterns, edge cases, and AI feature opportunities discovered during deployments.
* Monitor post-go-live and drive continuous improvement.