דרושים » הנדסה » AI Graph Compiler Engineer

In this role, you will be a key contributor to the design and implementation of 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 NPU embedded solutions, actively promoting 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.

As a Graph Compiler Software Manager, you will lead the development of next-generation graph compiler technology. This compiler is a cornerstone of AI software offering, empowering customers to optimize, map, and execute complex neural networks across 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 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.

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.

We are looking for an AI & Automation Engineer to design, build, and enable enterprise AI infrastructure and automation solutions.
This role focuses on AI architecture, workflow automation across IT and business applications, and monitoring, governance, and cost management of AI tools and agents.
You will work at the intersection of AI platforms, IT operations, and business automation, enabling scalable, secure, and cost-effective AI adoption across the organization.
Responsibilities:
Select and integrate AI tools, frameworks, and platforms aligned with enterprise IT standards.
Ensure scalability, security, reliability, and compliance of AI infrastructure.
Enable AI solutions from concept to production, including:
AI-powered IT tools
AI agents and copilots
AI services integrated into business applications
Collaborate with IT, DevOps, Security, and Business teams to deploy AI solutions smoothly.
Build reusable AI enablement patterns, templates, and best practices.
Automation of Workflows
Design and implement automation of IT and business workflows using AI and orchestration tools.
Integrate AI agents into:
IT operations (ITSM, monitoring, incident response)
Business applications and internal systems
Improve efficiency, reliability, and user experience through intelligent automation.
AI Monitoring, Usage & Financial Governance
Define and implement monitoring for AI systems, including:
Usage tracking
Performance and reliability
Model and agent behavior
Track and analyze financial usage and cost of AI tools, APIs, and platforms.
Establish governance frameworks for responsible and controlled AI usage.

In this role, as Embedded Software Team Leader, you will lead a software team taking major part in developing AI framework. This framework 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. 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.

Key Responsibilities:

Lead and manage the Embedded Software engineering team, ensuring high performance and productivity. Oversee the design, development, and implementation. 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.

You will participate in implementing a new strategic platform offering Generative AI (Gen AI) capabilities such as inference, fine-tuning, data curation, data labeling, and more.

We are seeking a highly skilled Gen AI software engineer to design, develop, and deploy state-of-the-art, scalable, efficient Gen AI solutions. You will be part of a high-performing engineering team that values collaboration, innovation, and teamwork. This role is perfect for someone who thrives in an environment where ideas are shared, challenges are met together, and success is a collective achievement.

Responsibilities:
Designed and implemented Gen AI platform components using Python and modern microservices.
Drive engineering and operational excellence and best practices.
Collaborate with tech, product, program, and business peers to deliver customer value and drive product vision.
Drive the end-to-end development of AI systems, from research and experimentation to deployment and scaling.
Mentor and support engineers, fostering a culture of collaboration, knowledge-sharing, and continuous learning.
Analyze complex problems and identify and define the requirements to solve them.
Apply DevOps principles to maintain high-performance and scalable AI systems.
Design and implement secure APIs, ensuring data protection and safe interaction with AI models.
Stay updated on the latest Gen AI trends and technologies, bringing fresh ideas to the team.

We are seeking a highly motivated High-Performance System Architect to join our team of experts and help shape the future of high-performance and ML / AI computing. Our next-generation NVL systems will be at the forefront of connecting and powering the world's most advanced compute clusters, which would be used to train the most advanced AI models such as GPT and DeepSeek. As a high-performance system architect, you will have the opportunity to work on some of the most cutting-edge technology and help to drive the innovation of our next generation networks that will be used by top researchers and engineers around the world.

What youll be doing:
Define the NVL system architecture end-to-end, by internal requirements and customers requirements through all product life cycles (post/pre silicon, on deployments).
Research various of solutions to enable the next large-scale-high-performance computing clusters. The position spans over various layers from algorithms, software, firmware, and HW.
Collaborate with cross-functional teams, including other architecture teams, logic design, system software, firmware, and research teams, to ensure the successful execution of the project.

seeking a hands-on Embedded Software Technical Lead to play a key role in the design and development of firmware for our next-generation rider products. This role is focused on deep technical ownership, system -level thinking, and high-quality implementation, and is ideal for an experienced Embedded engineer with a strong algorithmic background and solid architectural understanding-who can also mentor and lead a small team of 2-3 Embedded engineers while remaining highly hands-on in day-to-day development. What Youll Do
* Take hands-on responsibility for the design and implementation of Embedded software architecture for new wireless communication devices (ARM Cortex-M, RTOS, ultra-low-power systems).
* Design, implement, and optimize complex Embedded algorithms, including Real-Time control flows, communication logic, and audio/ DSP -related pipelines.
* Write, review, and maintain high-quality, production-grade C / C ++ code.
* Contribute to system -level architectural decisions and ensure scalable, robust firmware design.
* Define and promote coding standards, design patterns, and best practices across the firmware domain.
* Act as a technical focal point for debugging, root-cause analysis, and performance optimization of complex issues.
* Lead a small team of 2-3 programmers/engineers: provide technical direction, help with task breakdown and prioritization, and ensure high-quality delivery.
* Mentor engineers through design reviews, technical discussions, pairing, and hands-on collaboration-raising the teams engineering bar.
* Work closely with Hardware, QA, Mobile App, Cloud, and Product teams to deliver integrated, end-to-end solutions.
* Participate in technical roadmap discussions and evaluation of tools, technologies, and wireless stacks.

We are seeking an experienced IT/Lab Manager to lead the planning, deployment, and operations of our physical lab environment and IT systems. This role will focus on building and maintaining scalable, reliable, and secure environments to support engineering teams involved in research, quality assurance, validation, and related activities. It will also support internal collaborators. You will have an outstanding opportunity to drive innovation in a multidimensional, technology-focused company that is crafting the future of data-center and lab technologies. If you bring perfection and creative thinking while solving issues as they arise, and enjoy working with distributed teams - your place is with us!

What Youll Be Doing:
Own day-to-day operations, planning, and roadmap for the engineering lab and IT infrastructure (servers, storage, networking, and related services).
Lead and mentor an IT/Lab team, driving guidelines, standards, and a culture of ownership, partnership, and continuous improvement.
Collaborate closely with R&D, QE, Verification, and other engineering teams to design, provision, and maintain environments that meet their performance, reliability, and security needs.
Lead all aspects of running data center and lab operations, including rack layout, cabling, power and cooling, hardware lifecycle, and resource availability.
Lead procurement and vendor management for hardware, software, and services, including evaluation, negotiation, and ongoing relationship management.
Implement and maintain automation for system provisioning, configuration, and operations using tools such as shell/Perl/Ansible.
Design and maintain monitoring, logging, and alerting for servers, network, and storage systems to ensure high availability and rapid incident response.
Investigate and resolve sophisticated infrastructure issues across OS, networking, storage, virtualization, and application layers.