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In this role, you will be shaping the future of our companys AI software stack for Neural Processing Units (NPUs). You will lead software architecture, define performance-critical components, and enable efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
We are seeking a high-impact motivated Software Architect to join our team and help shape the future of our advanced neural network AI Software Toolchain over our companys AI computing processors.
Responsibilities
Lead Software Architecture specification and supervise design for the most advanced Software Toolchain handling state-of-the-art Neural Processing Unit operation.
Design and promote holistic software solutions incorporating various aspects of NPU handling: from network retraining, graph compiling and network inference execution on the embedded systems.
Collaborate proactively with Product, Architecture, VLSI and Software teams to promote software leadership over various markets and compute SoCs.
Explore and translate state-of-the-art neural network and AI applications requirements into software architecture flows, encompassing hardware, software, tools and other components.
Evaluate architecture proposals, internal and external IP features and provide influential and inspirational leadership across hardware and software to align all parties to a common vision of architecture & technology development.
Represent our company with high technical credibility in customer meetings, appropriately incorporating feedback.
Boost velocity of development teams by providing technical guidance and by constantly looking ahead to anticipate and resolve future challenges.
Conduct experiments, invent and drive development of supporting tools such as simulators, models, profilers, and other methods as required.
Engage with engineering leadership and product planning stakeholders to develop technology roadmap.

In this role, you will be a key contributor to the design and implementation of our companys AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the AI Graph Compiler software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

In this role, you will be a key contributor to the design and implementation of our companys AI Graph Compiler software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the AI Graph Compiler software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

We are looking for an Infrastructure Team Leader to lead and manage a highly skilled team of 4-5 engineers, responsible for Emulation, CAD, DevOps, compute infrastructure, and automation.
This role combines 50% hands‑on and 50% manageiral technical leadership and end‑to‑end ownership of infrastructure, tooling, and release flows.
The position has a significant impact on productivity, quality, and time‑to‑market of the companys silicon products and is reporting directly to the director of the department.
Responsibilities
Lead and mentor the Infrastructure team, including CAD, DevOps, automation, and emulation activities.
Own the definition, development, and maintenance of infrastructure: Emulation, design flows, verification flows, releases, automation, TFS Azure DevOps and CI/CD pipelines.
Drive continuous improvement of infrastructure reliability, performance, scalability, and usability.
Take end‑to‑end responsibility, cross BU, cross site VLSI releases, environments, and production readiness.
Collaborate closely with different stakeholders in the HW and SW RnD teams to align infrastructure with project needs.

we are at the forefront of AI inference and signal processing, powering some of the world's most advanced edge devices with our NPU, Connectivity, Wireless, and Sensing IP platforms. As part of our Customer Solutions Group, you'll join a senior team of technical experts who are the bridge between our company's engineering depth and the real-world needs of customers and partners worldwide.
This is a customer-facing role focused on our company's AI Division, spanning the full customer lifecycle, from pre-sales technical evaluation through post-sales integration. The role combines technical account management with disciplined operational follow-through on behalf of assigned customers.
You'll engage in complex, deeply technical conversations that require strong engineering understanding paired with the communication skills and gravitas to represent our company credibly to customers.
What you'll do
Act as the senior technical point of contact for assigned customers, representing our company credibly and in depth on our AI Division's product status, roadmap, and forward plans, including presenting technical material and traveling on-site as needed.
Own the operational flow of customer communications, triaging incoming requests, routing them to the right internal stakeholders, and driving each item to closure.
Proactively track all open commitments and milestones on behalf of assigned accounts, ensuring nothing slips and that customers receive timely, accurate status updates.
Support pre-sales technical engagements - demonstrating product value, evaluating customer use cases, and contributing to proof-of-concept efforts.
Guide customers through post-sales integration, helping them get the most out of our company's tools and software stack.
Maintain and grow the organization's knowledge base of customer environments, technical challenges, and solved cases.

In this role, you will learn and deeply understand the AI fundamentals and create tools and software that transform AI network into embedded implementation on our companys processors. In addition, you will perform in-depth analysis and optimization to the generated software and tools, to ensure the best performance and accuracy on various our company s processors architectures.
Responsibilities:
Taking part of innovative, agile, top-notch SW team, designing Neural Network Processor (NPU) graph compiler and software in close collaboration with the architecture, algorithms, system and hardware teams.
In addition You will take part in designing and developing software code for graph compiler for neural network processing and embedded system resources management.

We are seeking an experienced and commercially driven Director of Licensing to lead the licensing strategy and execution for our semiconductor intellectual property (IP) portfolio. This role is responsible for efficiently driving complex product and commercial contract negotiations with semiconductor manufacturers, fabless companies, and system integrators.
The ideal candidate combines proven experience in IP licensing (commercial and legal), technology commercialization, complex negotiation and business acumen, strategic deal making skills, with knowledge of the semiconductor industry being a plus.
Key Responsibilities
Portfolio Monetization & Licensing Strategy
Work closely with leadership in Product Divisions, Sales , Finance and Legal to develop strategies to maximize revenue from the companys IP portfolio.
Evaluate opportunities for licensing expansion, renewals, and new use cases.
Support IP valuation, competitive analysis, and market positioning.
Define optimal licensing models and pricing models that support and drive sustainable and profitable growth
Deal Structuring & Negotiation & Enforcement
Work closely with leadership in Product Divisions, Sales, Finance and Legal to develop and maintain commercial proposal templates and license agreement templates that increase and streamline deal process efficiencies and align with business objectives.
Support the Sales team globally throughout complex commercial and legal negotiations, from proposal to deal closing stages and manage contract lifecycle thereafter.
Coordinate with Sales, Finance and Legal teams on reporting, compliance, and enforcement of contract terms.

Lead a team of compiler engineers responsible for our company's 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 our company 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 our company's 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.

As a CAD Engineering Student, you will join an experienced CAD, DevOps, and Emulation team, working on cutting-edge VLSI infrastructure. You will support automation, release processes, and emulation flows while gaining hands-on exposure to full chip development environments.
Responsibilities:
Support VLSI infrastructure, automation flows, and release processes.
Assist in developing and maintaining CAD/DevOps scripts and tools
Participate in emulation activities and environment setup
Collaborate with design and verification teams to improve engineering efficiency.

As a Graph Compiler Software Manager, you will lead the development of our companys next-generation graph compiler technology. This compiler is a cornerstone of our companys AI software offering, empowering customers to optimize, map, and execute complex neural networks across our company architectures with extraordinary efficiency. You will lead a group of talented engineers and team leaders working across domains such as compiler optimizations, graph-level transformations, operator mapping, scheduling, and code generation. We are seeking a visionary and technically strong leader with passion for excellence and impact in one of the most fascinating areas of AI and deep learning.
Key Responsibilities:
Lead the design and implementation of innovative graph compilation flows for AI workloads, from high-level optimizations to hardware-specific backends. Build and guide a strong, innovative, and results-driven compiler team that thrives on solving complex technical challenges. Collaborate with hardware architecture, VLSI, and software framework teams worldwide to ensure seamless integration and maximum performance. Lead the end-to-end delivery of graph compiler components while meeting aggressive KPIs. Establish and execute group planning processes to ensure timely and high-quality delivery. Provide technical and managerial guidance to team leaders and engineers. Define and drive compiler optimization strategies for AI and deep learning workloads.

Lead the development of our company 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 our companys latest NPUs and DSPs - NeuPro-M, NeuPro-Nano and SensPro2 - positioning it as a cornerstone of our companys sensing and AI platform.
Key Responsibilities:
Lead and mentor a team of software engineers developing our company 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, you will be a key contributor to the design and implementation of our companys Edge AI software stack for Neural Processing Units (NPUs). You will take part in defining software architecture, implementing performance-critical components, and enabling efficient execution of advanced neural networks under tight power, memory, and latency constraints.
You will work closely with hardware and system architects, software and hardware engineers, influencing both software and hardware decisions. You will design and implement major parts of our company NPU embedded solutions, actively promoting our company AI capabilities to the customers.
What will you do:
Own and design key components of the Edge AI software stack for NPU-based systems.
Optimize inference performance (latency, throughput, memory footprint, power) for edge deployments.
Collaborate on HW-SW co-design, influencing NPU architecture.
Support IP evaluations and silicon bring-up, root-cause complex HW/SW issues, and influence development methodologies.
Mentor junior engineers and contribute to technical best practices.

Join our company's software tools team and contribute to widely used open source based toolchains while building tools that run on real hardware across millions of devices. Our team embraces an AI-agentic development flow - using AI coding agents as part of everyday engineering - and we want engineers who are excited to work this way from day one.
Responsibilities
Contribute to our company's open source based toolchain targeting custom DSP and NPU architectures.
Analyze and optimize toolchain output for performance and correctness across our company processor families.
Apply AI-agentic development practices in day-to-day work - using AI coding agents to accelerate development.
Collaborate with architecture, hardware, and software teams.

We're looking for a talented Software Engineer with enthusiasm for AI/GenAI to join our innovation-focused team building agentic AI systems autonomous, reasoning-driven software agents capable of orchestrating complex tasks across tools, APIs, and data sources.
You'll design and build scalable backend systems that integrate large language models (LLMs) and other AI technologies into production-grade services. This role blends backend engineering, AI integration, and rapid prototyping, with room to learn, experiment, and deliver impactful, scalable solutions.
Architect and implement distributed services that power AI-driven applications.
Implement multi-step reasoning pipelines, retrieval-augmented generation (RAG), and domain-specific AI capabilities.
Build robust APIs, plugins, and integrations enabling AI agents to interact with external systems and data sources.
Create and refine proof-of-concepts, validating ideas quickly before scaling to production.
Implement monitoring, evaluation, and logging systems to track AI-powered features in production.
Work closely with product managers, designers, data scientists, and AI engineers to deliver user-focused solutions.
Stay curious about emerging AI frameworks, tools, and best practices to improve reasoning, planning, and autonomy in backend services.