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We are looking for a software student that will take part in our software projects and practical research activities.

You will have the opportunity to learn and gain experience related to many aspects of software and hardware. In addition, we encourage you to have your final academic project done here.

responsibilities:

Maintaining, updating and debugging existing software tools, primarily in Python. This part is around 70% of the expected activity.

Taking part in architectural research and development. Including: developing test cases, executing and presenting results.

Modeling, running, and analyzing AI neural networks to evaluate their behavior and performance on Cevas DSP processors and AI accelerators.



We are looking for a CAD/Emulation Graduate Engineer to join our infrastructure team. This position is designed as an entry-level role for a recent graduate, providing hands-on experience with advanced VLSI CAD/Emulation and infrastructure



Key Responsibilities

Develop and maintain automation scripts for front-end Emulation and VLSI CAD flows and automation.

Support execution and releases of VLSI artifacts while marinating advanced CAD flows.

Assist in improving infrastructure efficiency and tool integration.

Work with version control systems and CI/CD pipelines for regression and build environments.

Own and rule top notch emulation methodologies and procedures.

Lead a team of compiler engineers responsible for open source based toolchain and graph compiler. You will be a hands-on team leader - driving architecture decisions, guiding engineers, and delivering compiler capabilities across all hardware targets. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for a leader who champions this approach.

Responsibilities

Lead development of open source based toolchain targeting custom DSP and NPU architectures. Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation. Champion AI-agentic development practices within the team - integrating AI coding agents into day-to-day engineering workflows. Mentor engineers and conduct code reviews; build a high-quality engineering culture. Collaborate with hardware architecture, algorithms, and software teams globally. Own team planning, prioritization, and on-time delivery of toolchain features. Contribute hands-on to design, implementation, and performance tuning in C++ and Python.

Lead the development of Sensing SDK, a core software toolkit that integrates a broad set of computer vision, audio, and voice libraries, along with AI operators. The SDK is specifically designed and optimized for latest NPUs and DSPs - NeuPro-M, NeuPro-Nano and SensPro2 - positioning it as a cornerstone of sensing and AI platform.

Key Responsibilities:

Lead and mentor a team of software engineers developing Sensing AI SDK. Architect and implement high-performance sensing SW components for AI, vision, Audio and voice optimized for vectorize SIMD execution. Collaborate with compiler and DevOps teams to ensure efficient development and deployment. Drive technical excellence through code reviews, design discussions, and continuous improvement. Own the SDK roadmap, planning, and delivery cycles. Engage with customers to enable successful pre-sale processes, support integration and gather feedback.

In this role, as Embedded Software Team Leader, you will lead a team owning a key part of NPU AI software stack, a complex, multi-layered system spanning the Host (SDK, runtime, APIs, and UMD/KMD drivers) and the NPU IP (embedded firmware). This stack is at the heart of the AI software offering, with deep impact on multiple hardware and software teams ability to execute state of the art LLM, Generative AI and Neural Networks with extraordinary performance. Reporting to the AI Software SDK Senior Team Leader, you will lead a team of creative and result oriented enthusiasts that invent, design, and implement software that enables smooth connectivity between the NPU and Host CPU.



Responsibilities:

Lead and manage the Embedded Software engineering team, ensuring high performance and productivity.

Own the design, development, and implementation of your component within NPU AI software stack, aligned with the AI Software SDK group's technical strategy, architecture, and roadmap and its automated CI and release process.

Collaborate with cross-functional teams to integrate solutions. Provide technical guidance and mentorship to team members.

Ensure project timelines and deliverables are met.

Conduct performance reviews and support professional development of team members.

Collaborate globally with architects, HW teams, NPU teams, and other developer teams

As the R&D Technical Project Manager you will lead large-scale, multidisciplinary programs developing Neural Network Processor (NPU) and AI IP products.

You will lead cross-functional engineering teams (30+ engineers) across architecture, algorithms, VLSI, embedded software, SW tools, and systems, ensuring seamless execution from Product Requirements Document (PRD) to production-ready delivery for leading SoC makers and OEM customers.

You will also act as the primary interface between customers, product team , and internal R&D teams , balancing technical leadership, strategic execution, and organizational excellence in a global, multi-site environment.

Responsibilities

Be accountable for successful planning and delivery, in quality, on time under budget, of all R&D programs & products in the AI Division, covering architecture, algorithms, hardware IP, embedded software, SW tools, and integration tasks.

Accountable for the definition and deployment of the AI Division Program development processes.

Program Planning and Execution

Own end-to-end planning and delivery for complex AI processor IP programs that include hardware design, embedded SW, and SW development tools.

Build and manage integrated schedules across RTL, verification, firmware, drivers, toolchain, and documentation.

Drive execution across concepts, design, verification, bring-up, and customer release phases.

Manage program POR, program priorities, and change control process.

Track dependencies between IP architecture, firmware readiness, SDK/toolchain availability, and customer enablement deliverables.

Define and manage program KPIs: schedule, quality metrics, and customer satisfaction.

As a senior compiler engineer, you will own the design and development of open source based toolchain and graph compiler. You will drive technical solutions end-to-end, deliver compiler capabilities across all hardware targets, and help mentor engineers. Our team embraces an AI-agentic development flow, leveraging AI coding agents to accelerate engineering productivity, and we are looking for engineers who champion this approach.

Responsibilities:

Design and develop open source based toolchain targeting custom DSP and NPU architectures.

Drive design and delivery of graph compilation flows: transformations, operator mapping, and code generation.

Champion AI-agentic development practices - integrating AI coding agents into day-to-day engineering workflows.

Own complex components end-to-end, from architecture and design through implementation and delivery.

Provide technical guidance and mentorship to engineers; conduct code reviews.

Collaborate with hardware architecture, algorithms, and software teams globally.

Analyze and optimize toolchain output for performance and correctness across processor families.

Innoviz Technologies is a global leader in LiDAR technology. Beyond automotive, Innoviz provides off-the-shelf LiDAR solutions for defense and homeland security, intelligent traffic management, mobility, robotics, and aerial applications. Innoviz Computer Vision Embedded Software team is responsible for the development of the software composing our computer vision solution. The team deals with the architecture and implementation of the most advanced elements per the standards of the automotive industry, dealing with the most advanced solutions in object detection and classification. We are looking for a talented Embedded SW Engineer to join our great team. Responsibilities
* Implementing the embedded SW for computer vision elements in the embedded solution.
* Feeding the algorithm team with constraints and implementation details related to the embedded implementation. **This is a great opportunity for experienced embedded engineers to get into the exciting and evolving fields of computer vision and autonomous driving.

Sub Department:
Algorithms

City:
Rosh Ha‘Ayin

Join an agile team working on the most advanced wireless communication solutions, focused on the latest communication standards. You will define the architecture for future products and optimize modem solutions for hardware implementation.

Responsibilities:

Research and define architecture for advanced communication standards.

Define PHY System specifications and architecture for future solutions.

Define low-power architecture.

Work closely with the functional teams (Algorithm, HW/SW, RF, Validation, etc.), from early algorithm study to system validation.

Participate in integration and testing of wireless system solutions, spanning embedded SW, HW and radio.

Support customers engagement and product deployment.

we are looking for a Runtime Sensor Developer | eBPF Expert.
In this role, youll write low-level code that hooks deep into runtimes and OS internals (via eBPF) to capture runtime data with near-zero overhead. Basically, youre creating the eyes and ears inside applications, so we can detect intrusions as they happen.
Youll be pushing the envelope of what eBPF and kernel tech can do: tracing syscalls, monitoring network flows, and intercepting anything attackers might exploit. Your work will help determine exploitability and flag compromises instantly - even for zero-day attacks that nobody has seen before.
This is a high-impact, experimental role: part engineer, part hacker - optimizing for performance and reliability while youre bending the rules of the OS. If you love digging into assembly, performance tuning, and building tools that peer into the guts of running software, come join us. Youll have the freedom to innovate at the lowest levels of the stack (and we promise, no boring corporate kernel modules here - only the fun stuff!).

we are looking for a Senior Backend Engineer.
What you'll do:
Design and scale event-driven streaming systems using Kafka and Temporal to enable real-time security analysis and decision making.
Build rule-based and data-driven pipelines that turn application signals into actionable detections.
Collaborate with product, integrations, and detection teams to create new data flows that unlock innovative security capabilities.
Lead improvements in scalability, reliability, and observability to keep the pipeline ahead of growth and complexity.

we are looking for a Senior Full Stack Engineer with a backend-oriented mindset to join our growing R&D team.
In this role, youll be responsible for connecting high-scale data infrastructure with our customer-facing portal-turning complex, runtime telemetry into fast, intuitive, and intelligent user experiences. Youll work closely with product, design, and Data pipeline and security engineers to build data pipelines, APIs, and integrations that make platform both powerful and delightful to use.
This is a hands-on role at the intersection of backend systems, high scale data engineering, and user experience, shaping how massive volumes of runtime data flow through data-driven platform.
Youll Be Great For This Role If You Love To:
Design and implement efficient data pipelines and backend integrations that connect our high-scale data to the user-facing portal.
Build and optimize APIs, data services, and caching layers to ensure fast and reliable data access.
Use data modeling, denormalization, and performance optimization to handle complex queries and large datasets effectively.
Collaborate closely with frontend engineers, product managers, and designers to ensure data flows seamlessly into intuitive UI components.
Contribute to the architecture and scalability of hybrid cloud-native platform.
Write clean, testable, production-ready code in Python, Node.js, TypeScript, and React, while keeping performance and maintainability top of mind.
Stay close to users and product feedback loops - helping translate technical insights into better experiences.
Own end-to-end delivery, from backend design through deployment using CI/CD, Temporal, and Kubernetes.

we are looking for a Senior Backend Engineer with a strong passion for AI and intelligent systems to join our growing R&D team.
In this role, youll be building the backend foundation that powers our AI-enhanced security analytics, autonomous detection, and real-time decisioning systems. Youll work closely with AI engineers, product, and security experts to bring agentic intelligence into runtime platform - transforming how modern apps defend themselves.
Youll architect and implement services that scale to massive volumes of runtime data, integrate large language models (LLMs), and support RAG-based workflows for contextual understanding and response.
Youll Be Great For This Role If You Love To:
Design and build scalable, resilient backend services that power AI-driven runtime security platform.
Integrate LLMs and agentic AI components into production environments to enable autonomous detection and remediation capabilities.
Design evaluation frameworks for measuring model performance and reliability in real-world conditions.
Develop Retrieval-Augmented Generation (RAG) pipelines tailored to application security data.
Own backend architecture decisions - from data modeling to performance optimization - across Node.js, Python, and cloud-native environments.
Contribute to our infrastructure, leveraging CI/CD, Kubernetes, Docker, and modern observability practices.
Mentor peers and help shape AI engineering culture.

We're looking for an AI Tech Lead to own that standard across three surfaces:
The platform - Today each agent flow is close to a bespoke implementation. You'll turn our hard-won patterns into shared components, conventions, and infrastructure so the next agent is a week of work rather than a quarter - with evaluation, observability, and cost control built in rather than bolted on.
Enablement - Miggo's advantage compounds only if the whole company is AI-fluent, not just R&D. You'll raise that fluency everywhere - engineering, research, product, GTM - through tooling, patterns, and teaching.
The voice - You'll publish the methodology: how we benchmark agentic security output, how we model residual risk, what we learned failing. This is a category-defining position and we want it argued in public.
This is a hands-on lead role with no direct reports. Your authority comes from the quality of what you build and how clearly you explain i