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Description
Location: Tel Aviv
#Hybrid
DriveNets is a leader in high-scale disaggregated networking solutions. Founded in 2015, DriveNets modernizes the way service providers, cloud providers and hyperscalers build networks. Supporting the largest network in the world, more than half of AT&T’s backbone traffic is running on DriveNets’ Network Cloud open disaggregated architecture. Raising $587 million in three funding rounds, DriveNets is disrupting the networking market from high-scale architecture to AI platforms, and is bringing onboard the most talented people. We are seeking people that want to make an impact on the world’s leading communication networks and are experienced in networking architecture or AI infrastructure solutions.
Job Summary
We are seeking an experienced technical leader to head our collective communication library development team. This role involves leading a team of engineers in developing high-performance collective communication implementations for multi-NPU and multi-node AI workloads.
Key Responsibilities
Lead the design and development of collective communication primitives (All-Reduce, All-to-All, Gather/Scatter and etc)
Architect scalable communication protocols for multi-NPU and multi-node systems
Optimize communication performance for NPU architectures
Provide technical leadership to the team members in NPU programming, distributed systems, and communication protocols
Work with a success-driven worldwide international team (Network, NPU, QA, AI, DL/ML Framework)
Define project milestones, deliverables, and technical roadmaps
Ensure compatibility with major AI frameworks (PyTorch, TensorFlow, JAX)
Requirements
Required Qualifications
BSc/MSc in computer science/computer engineering or equivalent
8+ years of experience in systems programming and distributed computing
5+ years of leadership experience managing technical teams
Expert-level C/C++ programming with focus on performance optimization
Experience with NPU programming (Triton / CUDA / HIP / OpenCL)
Deep understanding of distributed systems, communication protocols, and network programming
Experience with DL/ML frameworks (PyTorch, TensorFlow) and distributed training / inferencing
Experience with performance profiling and optimization tools
Strong communication and interpersonal skills
Preferred Qualifications
Experience with NPU communication library development
Contributions to open-source projects (PyTorch, TensorFlow, communication libraries)
Familiarity with containerization and orchestration
Interoperability experience with partners, vendors and external teams
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