דרושים » ניהול ביניים » Staff Engineer, AI Software Embedded Engineer - Hod Hasharon

Experienced DSP & AI Development Engineer

Engineering, DSP, Communications, AI, Embedded Software, Algorithms

Location Israel - Hod HaSharon

Responsibilities
Design and develop high‑performance DSP software, including highly efficient kernels for different applications, such as communication algorithms and machine learning inference workloads

Implement optimized, low‑level DSP solutions with a strong focus on performance, accuracy, and real‑time constraints

Deliver high‑quality, efficient, and well‑tested code according to project schedules

Collaborate closely with team members and peer teams across multiple engineering disciplines

Our team at the Huawei Computing Network Innovation Lab is looking for exceptional talent to join us and lead the development of next-generation data centers. We create cutting-edge technologies that synergize software and hardware in tandem to accelerate compute, storage, and networking at large scale. We aim to drive innovation and deliver software-defined infrastructure and algorithms for HPC, AI/ML, and Big Data applications.
We are looking for an outstanding Research Team Lead with deep hands-on expertise in large-scale distributed systems, AI framework infrastructure, and performance optimization on custom accelerators. If you are a visionary technical leader, a skilled communicator, and a team builder who thrives at the frontier of systems and AI research - you're welcome on board.

What Will You Be Doing?
Lead and grow a world-class team of researchers and engineers working on distributed AI infrastructure and systems software.
Architect and own the software infrastructure enabling distributed training and inference on Huawei's custom accelerator hardware (e.g., Ascend NPU).
Drive research and development on communication libraries, runtime systems, memory management, and graph execution & synchronization at scale.
Optimize end-to-end performance across large-scale clusters, covering both scale-up (multi-device) and scale-out (multi-node) configurations.
Design and implement high-performance communication backends and collective operations (AllReduce, AllGather, broadcast) for distributed training workloads.
Collaborate cross-functionally with hardware architects, compiler teams, and framework engineers to co-design hardware-software solutions.
Publish and present research findings at top international venues (NeurIPS, EuroSys, SC, MLSys, OSDI) and represent the team externally.
Mentor engineers and researchers, conduct performance and growth reviews, and shape team culture and technical direction.
Partner with top academic institutions and open-source communities to advance the state of the art in distributed AI systems.

Next-gen Communications DSP & AI Software Development Engineer

Job Area

Engineering, DSP, Communications, 5G/6G, Algorithms, AI, Embedded Software

Location

Israel - Hod HaSharon

Responsibilities
Design and develop high-performance DSP software and optimized vector-processing kernels for wireless communications and AI workloads.
Implement low‑level DSP software with strong focus on performance, accuracy, and real‑time constraints.
Deliver high-quality, maintainable, and well-tested code while meeting project milestones.
Collaborate with team members and peer teams across multiple engineering disciplines.

We are looking for an experienced Tech Lead to lead a team of 3-5 software engineers developing innovative database security and data protection solutions for enterprise platforms.

This is a hands-on technical leadership role focused on cybersecurity, data security, and advanced software engineering. The successful candidate will combine deep security expertise with strong software architecture skills to define technical direction, lead engineering execution, mentor developers, and build enterprise-grade security solutions.

The role requires strong technical ownership, the ability to solve complex security challenges, and close collaboration with security researchers, product teams, customers, and engineering organizations. Occasional travel may be required for technical discussions and customer engagements.

Responsibilities
Lead and mentor a team of 3-5 software engineers, providing technical guidance and driving engineering excellence.
Define software architecture, technical strategy, and development direction for database security products.
Design and develop advanced cybersecurity and data security solutions for enterprise environments.
Lead security architecture discussions, technical design reviews, and code reviews.
Translate complex security requirements and research concepts into practical, scalable software solutions.
Drive secure software development practices across architecture, design, implementation, and deployment.
Solve complex technical challenges related to security, reliability, scalability, and performance.
Collaborate with security researchers, product management, and cross-functional engineering teams.
Participate in customer-facing technical discussions and occasional international travel.
Remain hands-on and contribute to critical software components and technical decisions.

Our Tel Aviv Research and Innovation Center, is looking for an experienced software engineer with expertise in Linux kernel and virtualization design + development to join our Future-Computing-Infrastructure expert group. The group designs and develops technologies for the next-generation data center aimed at accelerating AI workloads for a unique HW, optimizing compute resource utilization and reducing data-center costs. Our projects involve hardware and software architecture co-design. They require high-level system understanding, creativity and innovative thinking.
If you want to be part of something bigger, if you are a team player with excellent communication skills and motivation to revolutionize data-center technology, youre welcome on board!


What will you be doing?
Design and develop Linux kernel code related to virtual memory management and memory-tiering.
Research, design and innovate methods, algorithms and supporting data-structures for managing memory hierarchies in virtualization environments
Participate in research to analyze AI-based applications performance, identify bottlenecks and optimize various decision-making mechanisms based on benchmarking results.
Collaborate with professional team members and various global teams around the world on a daily basis.
Challenged to think outside of the box and come up with creative ideas to deal with complex challenges within Linux kernel.

We are looking for a Principal Engineer with deep expertise in database internals, system architecture, and hardware-aware performance optimization.
This role is responsible for defining and driving advanced database performance solutions by understanding and improving the interaction between database engines, operating systems, and modern hardware architectures.
The ideal candidate is an experienced technical leader with a strong background in database systems, performance engineering, and computer architecture. The candidate should be capable of leading complex technical initiatives, influencing architectural decisions, and developing innovative solutions for next-generation database platforms.
This is a hands-on technical leadership role requiring expertise across database kernels, query execution, transaction processing, memory systems, and low-level performance optimization.

Responsibilities
Define and drive technical direction for database performance optimization and hardware-aware database architecture.
Lead the design and implementation of advanced database optimizations focused on scalability, efficiency, and workload performance.
Solve complex performance challenges across the full system stack, including database engines, query execution, transaction processing, concurrency control, storage engines, operating systems, and hardware platforms.
Design and develop optimizations leveraging modern hardware architectures, including multi-core CPUs, large-memory systems, NUMA platforms, CXL memory, RDMA networking, and advanced storage technologies.
Improve database execution engines, caching mechanisms, memory management, storage systems, and workload scheduling.
Analyze system behavior and identify bottlenecks using profiling, tracing, hardware performance counters, and low-level performance analysis.
Develop benchmarks, workload models, and methodologies to evaluate scalability, efficiency, and architectural tradeoffs.
Collaborate with database kernel, infrastructure, and engineering teams to influence architecture decisions and deliver high-impact improvements.
Mentor senior engineers and contribute to building technical expertise across the organization.
Drive innovation through research, prototyping, technical analysis, and architectural improvements.

*Part-Time or Full-Time Opportunity

Responsibilities:
The research focuses on designing next-generation rack and SuperPod architectures that combine elasticity through resource pooling with optimal performance enabled by holistic co-design across applications, parallel programming models, interconnect fabrics, and compute, memory, and switch chip architectures. On the communication side, the work architects scalable, high-bandwidth, and low-latency scale-up fabrics across multiple chips at rack and SuperPod scale. On the memory side, it explores richer protocol semantics beyond traditional load/store operations to reduce unnecessary data movement and rethinks memory hierarchies to expose large-scale capacity with near-local latency. On the compute side, it analyzes the requirements of General Compute and Generative AI workloads and their parallel programming models to fully leverage large-scale system resources.
Investigate and prototype new architectural features, including but not limited to:
o Tiered Memory: Explore advanced memory organizations, including hardware-managed caching, to enable software-transparent, fine-grained promotion and demotion of cache lines across the memory hierarchy.
o Prefetching/Speculation: Evaluate and design existing and next-generation hardware prefetching and speculation mechanisms to effectively hide local and remote memory latencies at rack and SuperPod scale.
o Near-Memory/Network Processing: Develop support for key primitives executed at the memory and network layers to minimize unnecessary data movement across sparse, dense, and pointer-based data structures.
o Workload-Centric Co-Design: Study optimal parallelization strategies at rack and SuperPod scale for both General Compute and Generative AI workloads, and design dedicated hardware support for widely used parallel programming primitives such as RPCs and collective communication.
Write reports and papers on the research results and present them.

We are looking for a DevOps Engineer to turn expertise, initiative, and bold thinking into real impact on the next generation of AI-driven financial crime detection.



In this role, you will design and automate our cloud infrastructure and on-premises OpenShift environments - building the tools and processes that let our R&D team develop smoothly and rapidly, while helping maintain production stability through on-call support.



If you combine strong DevOps and infrastructure automation expertise with a passion for continuously improving tools and processes, and if you are motivated by keeping mission-critical systems fast, stable, and reliable for the world's leading financial institutions, could be your next challenge.



Responsibilities:

Continuously improve the tools and processes used by our R&D team to enhance productivity and innovation.
Design, implement, and automate our cloud infrastructure alongside on-premises OpenShift environments.
Provide our R&D and Production teams with robust, reliable tools to ensure smooth and quick workflows.
Research and explore new technologies and methodologies to continuously improve our development processes and overall product quality.
Participate in an on-call rotation, assisting lower tiers to mitigate issues and maintain system stability.

*Part-Time or Full-Time Opportunity

In this job opening, we are seeking a highly motivated and visionary researcher to join our team focused on chiplet-based computing systems. This role involves research and development in chiplet-based architectures, aiming to overcome performance and scalability limits of traditional compute platforms.

Responsibilities:
Conduct cutting-edge research on the co-design of communication and computation for wafer-scale systems. On the communication side, the work focuses on architecting Networks-on-Chip, providing scalable, high-bandwidth, and ultra-low-latency interconnects that efficiently span multiple dies and support fine-grained data movement. On the computation side, the research emphasizes optimizing and mapping training and inference workloads to fully exploit wafer-scale resources, improving performance, scalability, and energy efficiency through intelligent task placement and scheduling.
Investigate various aspects of system design, including:
Network-on-Chip design, further including Topology exploration, routing algorithms, and protocol/flow-control design to support high-throughput collective communication, low-latency synchronization, and efficient model/data parallelism
Expressing and Mapping LLM Parallelism to Wafer-Scale System that simplify LLM parallelism (e.g., tensor, pipeline, and data parallelism) and efficiently map training and inference workloads onto wafer-scale system

We are seeking a Data Engineer with strong technical expertise and a business-oriented mindset to lead end-to-end data, automation, and AI solutions. The role requires the ability to understand business needs and translate them into scalable, reliable technology solutions.

The successful candidate will design, develop, and maintain data pipelines, automation processes, analytics, and AI-enabled solutions that drive operational efficiency and data-informed decision-making. Strong collaboration, teamwork, and communication skills are essential, including fluency in English and the ability to work effectively with both technical and business stakeholders in a local and global environment.

Experience with Microsoft technologies (e.g., Azure, Power Platform, Power BI, Copilot) is a strong advantage. The position combines hands-on data engineering with automation, analytics, and AI innovation.