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Requirements:
Basic Qualifications
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design.
- Strong experience in software development.

Preferred Qualifications
- Experience with full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- An interest or experience in the field of Computer Vision and/or Recommendation Systems.
- Experience of or interest in working with applied science teams and deploying ML model in scale.
- Strong bias for action; ability to juggle multiple priorities and create a sense of urgency in a fast-paced, dynamic environment.

Requirements:
Preferred Qualifications:
- Experience in software development.
- Experience in the following fields is preferred:
- RT embedded SW.
- Multi-core CPU programming.
- C++ design knowledge.
- Performance analysis.

Requirements:
* Experience in End to End project management of multidisciplinary (Software/Hardware) products that were successfully delivered to international customers - MUST
* Experience working in a start-up - Preferred
* Experience building project Gantts/detailed schedules
* Experience in budget management
* Experience in product life cycle management
* BSc. / MSc. in Engineering, or any scientific field from a leading university
* Exceptional interpersonal skills
* Strong written and verbal communication skills in Hebrew and English

Requirements:
B.Sc. or higher in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field
8+ years of experience in systems software, distributed computing, or AI infrastructure, with 3+ years in a leadership or team lead role
Deep expertise in large-scale communication systems: collective communication, RDMA, network topology-aware routing, and bandwidth optimization
Hands-on experience building software infrastructure for distributed training on custom accelerators or heterogeneous hardware (GPU, NPU, TPU)
Strong knowledge of runtime systems: scheduling, execution graphs, kernel dispatch, synchronization primitives, and pipeline management
Experience with memory management at scale: activation checkpointing, tensor offloading, rematerialization, KV cache management
Proficiency in C/C++ and Python, with a focus on high-performance, production-quality code in Linux environments
Proven ability to define technical vision, lead multi-person projects end-to-end, and deliver results under research and engineering timelines
Excellent communication skills in English - confident presenting to international audiences, writing technical reports, and driving cross-team alignment
Strong collaborative mindset and experience working in globally distributed, multicultural teams
Ways to Stand Out From the Crowd
M.Sc. or Ph.D. in a relevant field, with a strong publication record at systems or ML venues (EuroSys, OSDI, SC, NeurIPS, MLSys, ISCA)
Hands-on experience with communication frameworks such as NCCL, MPI, HCCL, or UCX
Experience with compiler and graph optimization for AI workloads (XLA, TVM, Triton, or custom operator fusion)
Background in mixed-precision training, model parallelism (Tensor Parallelism, Pipeline Parallelism, Expert Parallelism), and large model co-design
Experience profiling and debugging performance bottlenecks on heterogeneous clusters using tools like Chrome tracing, nsight, or custom profilers

Requirements:
B.Sc. or higher in Computer Science, Computer Engineering, Electrical Engineering, or a closely related field
8+ years of experience in systems software, distributed computing, or AI infrastructure, with 3+ years in a leadership or team lead role
Deep expertise in large-scale communication systems: collective communication, RDMA, network topology-aware routing, and bandwidth optimization
Hands-on experience building software infrastructure for distributed training on custom accelerators or heterogeneous hardware (GPU, NPU, TPU)
Strong knowledge of runtime systems: scheduling, execution graphs, kernel dispatch, synchronization primitives, and pipeline management
Experience with memory management at scale: activation checkpointing, tensor offloading, rematerialization, KV cache management
Proficiency in C/C++ and Python, with a focus on high-performance, production-quality code in Linux environments
Proven ability to define technical vision, lead multi-person projects end-to-end, and deliver results under research and engineering timelines
Excellent communication skills in English - confident presenting to international audiences, writing technical reports, and driving cross-team alignment
Strong collaborative mindset and experience working in globally distributed, multicultural teams

Requirements:
Master in Electrical Engineering, Computer Engineering, Computer Science, or a closely related field.
Background in interconnection networks and computer architecture is a must.
Demonstrated research expertise in one or both of the following areas:
Network-on-Chip (NoC) architecture, including routing, flow control, topologies, and performance modeling
LLM parallel execution and co-design, including workload decomposition, communication-computation overlap, and mapping to high-performance interconnects
Excellent analytical, problem-solving, and system-level thinking skills.
Excellent programming skills with hands-on experience in simulator modeling, development and simulator-based evaluation.
Strong verbal and written communication skills, and the ability to work both independently and collaboratively in a cross-disciplinary team.