לוח משרות דרושים AI Engineer ברעננה, לחיפוש זה נמצאו 8 משרות

In this role, you will learn and deeply understand the AI fundamentals and create tools that simulate our companys AI neural network processor implementation.
In addition, you will perform in-depth analysis and optimization to the simulator, to ensure simulator performance and accuracy for various companys processors architectures.
The project is using C/C++ OOP as main development language as well as python for AI neural network.
Development platforms are Linux and Windows based.
Responsibilities:
Taking part of innovative, agile, top-notch Software organization, designing Neural Network Processor (NPU) simulator in close collaboration with the architecture, algorithms, system and hardware teams.
Design and develop simulation software solutions allowing our company customers to run most advanced AI networks efficiently on our company NPU software simulation.

In this role, as Embedded Software Team Leader, you will lead a team owning a key part of our company's 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 company 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 our company's 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.

You will be a key contributor to our companys AI Graph Compiler software stack for NPUs, designing system-level execution flows for advanced neural networks, including LLMs.
The role focuses on L1/L2 memory management, data movement, and performance optimization, working closely with compiler and hardware architects.
What will you do:
Design and own key components of our companys AI Graph Compiler.
Develop and optimize neural network execution flows and memory management.
Enable complex AI workloads, including LLMs, and implement new NPU features.
Analyze performance bottlenecks and drive system-level optimizations.
Collaborate with compiler and hardware teams on HW-SW solutions.

In this role, you will build deep expertise in AI fundamentals, LLM and generative AI network architectures, and their underlying algorithms. You will continuously research emerging generative AI architectures across the industry, staying ahead of how the field evolves.
A central focus will be quantization - understanding, developing, and refining quantization methods and algorithms, and driving their deployment on our hardware to achieve maximum performance without compromising accuracy.
Responsibilities:
Explore and plan end to end network deployment on our company's hardware.
Own network accuracy measurement and improvement.
Develop the graph compiler's hardware-aware quantization tool.

We're looking for an AI Specialist Engineer to join our AI Enablement team. This is a high-impact role where you will build products and internal tools used across the entire company, while working with the most advanced AI tools and best practices available today.
Key Responsibilities
Develop internal AI-powered products and tools used by teams across our company to work faster and smarter.
Lead the evaluation, integration, and rollout of AI-powered development tools across engineering teams.
Build proof-of-concept projects and internal tooling that demonstrate the practical value of AI in real workflows.
Develop best practices, prompt engineering guidelines, and training materials for AI-assisted development.
Stay current with the rapidly evolving AI tooling landscape and advise leadership on strategic adoption.
Work hands-on with the most advanced AI development tools and shape how the company uses them.

We're looking for an AI Workflow Engineer to join our System Architecture group. This is a high-impact role where you'll design, build, and continuously improve AI-powered workflows, agents, and tools that help our architects do their best work - from system design and modeling through documentation, technical decision-making, and review.
Working from within the architecture team, you'll turn the group's real, day-to-day pain points into practical AI-assisted solutions. Your primary focus is system architecture within the software development lifecycle (SDLC), and because architecture touches everything, your work will naturally extend into adjacent stages wherever AI can add value.
Key Responsibilities:
Design and build AI-powered workflows, agents, and internal tools that support system architecture work - design, modeling, documentation, architecture decisions, and reviews.
Develop and iterate on agents within our internal framework, using agentic AI techniques to accelerate and augment architecture and engineering tasks.
Continuously improve existing workflows and tools as team needs evolve and AI capabilities advance.
Partner closely with the System Architecture team to understand real pain points and turn them into practical, AI-assisted solutions.
Measure and demonstrate the impact of the workflows you build - for example on design-cycle time, review turnaround, and the quality and completeness of architecture documentation and decision records.
Build proof-of-concept projects that show the practical value of AI in real architecture and engineering workflows.
Develop best practices, prompt engineering guidelines, and reusable patterns for AI-assisted architecture and development.
Stay current with the rapidly evolving AI tooling landscape and advise on strategic adoption.