דרושים » תוכנה » AI & Automation Engineer

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 looking for an outstanding Senior Technical instructor to join our Education Services team. In this role, you will provide advanced training on our data center, AI, and HPC platforms to customers and partners around the world. You will also contribute to developing training content, including presentation decks, hands-on manuals, and supporting materials. You will help engineers, architects, and operations teams build the skills needed to design, deploy, and operate our-powered AI data centers with confidence. As part of this, you will take part in the design of hands-on workshops and lab environments that simulate real systems and data center components, enabling learners to practice on realistic end-to-end scenarios.

What youll be doing:

Deliver in-person and remote technical training on our data center, AI, and HPC platforms for customers and partners, with up to 25% travel as needed.

Lead lab-based training sessions that walk learners through end-to-end workflows on our GPUs, DGX/GB200 systems, high-speed networking, and AI/HPC software stacks.

Collaborate with internal experts and content developers to build agendas, exercises, and demos that reflect real customer use cases and guidelines.

Serve as a subject-matter guide (SME) for a dedicated production team and learning developers. They build primary content. Partner with them on slideware, lab guides, videos, simulations, visual demos, and exercises. Ensure technical accuracy and realism.

Act as a technical ambassador for us in front of partner and customer audiences, answering inquiries, facilitating discussions, and guiding learners through fix and what-if scenarios.

A new type of finance role designed for an AI-driven organization. You will combine strong FP&A fundamentals with curiosity for GenAI tools, modern analytics, and SaaS monetization. Working closely with AI leaders, product teams, and business stakeholders, you will help translate innovation into financial insights while contributing to core financial execution.

What will your job look like?
Support planning, forecasting, and performance analysis for Data & GenAI initiatives
Build financial models for AI solutions, SaaS offerings, and data-driven business cases
Analyze monetization approaches for GenAI-driven capabilities and internal transformation programs
Design and track KPIs measuring efficiency, productivity, and value from AI adoption
Partner closely with product, engineering, and AI leaders to translate roadmaps into financial narratives
Use GenAI and analytics tools to streamline reporting and improve decision-making workflows
Maintain ownership of core FP&A deliverables while supporting strategic decision-making

The AI Graph Compiler Engineer will design and develop next-generation graph compiler technologies enabling efficient execution of advanced AI models on Neural Processing Units (NPUs) used in edge and embedded AI devices. In this role, you will work at the intersection of AI frameworks, graph optimization, and hardware acceleration, enabling efficient execution of neural networks on cutting-edge AI hardware.

You will work at the intersection of AI frameworks, compiler infrastructure, and hardware acceleration, helping translate high-level AI models into highly optimized executions on NPUs.



What will you do:

Develop and enhance AI graph compiler components targeting NPU architectures. Implement graph-level optimizations such as operator fusion, scheduling, memory planning, and layout transformations. Participate in lowering models from AI frameworks (e.g., PyTorch, ONNX, TensorFlow) into NPU-optimized representations. Contribute to compiler passes focused on performance, memory efficiency, and numerical correctness. Collaborate closely with hardware, runtime, and AI framework teams to achieve optimal end-to-end performance. Analyze performance bottlenecks and assist in compiler-based optimizations. Debug and resolve issues across compiler, runtime, and hardware layers. Support testing, validation, and documentation of compiler features.

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.

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.

We are looking for an experienced Software Engineer to join our team with a focus on services and infrastructure development, while being comfortable contributing across the full software stack when required.

This role is well suited to an engineer who enjoys designing and building scalable backend services, integrating them with infrastructure platforms, and contributing to end-to-end solutions that support sophisticated engineering workflows. While some components may include frontend elements, the primary emphasis is on service architecture, APIs, data handling, and system reliability.

In this role, you will collaborate closely with engineers and partners across the organization to design, deliver, and evolve maintainable solutions that underpin GPU software engineering infrastructure. You will also contribute to technical direction, mentor others, and help shape the long-term evolution of our platforms.

Responsibilities:
Design, develop, and maintain scalable backend services using Python, Go or similar languages, with the ability to contribute to full-stack solutions where appropriate.
Take ownership of services across their lifecycle, from design and implementation through deployment and production support.
Design and evolve APIs and service interfaces that support tooling, automation, and infrastructure workflows.
Contribute to end-to-end feature development, spanning backend services, APIs, and selective frontend components where they support infrastructure use cases.
Collaborate closely with teams across tooling, automation, and infrastructure to ensure seamless service integration.
Improve system reliability, performance, and scalability through thoughtful design and continuous optimization.
Contribute to infrastructure modernization initiatives, including cloud-based and containerized deployments.
Follow and promote standard methodologies for code quality, testing, documentation, and design reviews.

We are looking for a Senior HPC and AI Cluster Administrator to join the Networking clusters solutions HPC/AI Infrastructure team. We are building supercomputers and AI clusters based on groundbreaking technologies. We are looking for a system administrator to be a key player to the most exciting computing hardware and software to contribute to the latest breakthroughs in artificial intelligence and GPU computing

You will work with the latest Accelerated computing and Deep Learning software and hardware platforms, and with many scientific researchers, developers, and customers to craft improved workflows and develop new, leading differentiated solutions. You will interact with HPC, OS, GPU compute, and systems specialist to architect, develop and bring up large scale performance platforms. Does this sound like you? If so, we would love to hear from you!

What you will be doing:

Deploy, manage and maintain large scale HPC/AI clusters.

Managing Linux job/workload schedules and orchestration tools.

Support and maintain continuous integration and delivery pipelines.

Troubleshooting and fixing, bottom up from bare metal, operating system, software stack and application level.

Supporting Research & Development activities and engaging in POCs/POVs for future improvements.

We are looking for a highly professional Technical Marketing Engineer (TME), to dive into our technology, master our lab and produce high-quality technical marketing content for our AI-infrastructure marketing campaigns. This position plays a crucial role in translating our engineering know-how into marketing content. It requires a blend of deep networking technical expertise, hands-on capabilities, strong communication skills, and a passion for translating complex technical information into compelling marketing messages that resonate with target audiences.
Responsibilities 
Collaborate with our research lab, engineering and delivery services to map technology, architecture, and deployment know-how.
Create high-quality content (reference designs, deployment and configuration guides, whitepapers, case studies, blog posts, demos etc.)
Support sales and channels in customers and partners' meetings.
Travel to support tradeshows, and customers and partners' events.

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.