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במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
מלאה
25,000-40,000 ₪
We seek a versatile Senior Software Engineer who is passionate about performance optimization and generative AI. Our team brings the latest research in LLM inference - from novel decoding strategies to quantization schemes - into production across Our hardware lineup, from large data center servers to powerful edge devices. We work on the most advanced architectures in the field, with a focus on our own.
What you'll be doing:
Implement and optimize inference algorithms for LLM and omnimodal architectures, including hybrid Mamba-Transformer and mixture-of-experts models
Profile inference pipelines using our profiling and simulation tools. Correlate simulation predictions against real hardware across data center and edge devices
Write and tune GPU kernels (CUDA, Triton) for operators like fused MoE layers, SSM state updates, and quantized GEMMs
Solve distributed inference problems: expert parallelism, communication-compute overlap, collective tuning, multi-node deployment
Build production-grade software inside major open-source libraries - vLLM, SGLang, Dynamo, FlashInfer
Own optimization features end-to-end, from scoping through delivery, collaborating with research, product, and engineering teams worldwide.
What you'll be doing:
Implement and optimize inference algorithms for LLM and omnimodal architectures, including hybrid Mamba-Transformer and mixture-of-experts models
Profile inference pipelines using our profiling and simulation tools. Correlate simulation predictions against real hardware across data center and edge devices
Write and tune GPU kernels (CUDA, Triton) for operators like fused MoE layers, SSM state updates, and quantized GEMMs
Solve distributed inference problems: expert parallelism, communication-compute overlap, collective tuning, multi-node deployment
Build production-grade software inside major open-source libraries - vLLM, SGLang, Dynamo, FlashInfer
Own optimization features end-to-end, from scoping through delivery, collaborating with research, product, and engineering teams worldwide.
Requirements:
B.Sc., M.Sc., or equivalent experience in Computer Science or Computer Engineering
5+ years of hands-on software engineering experience in performance-critical systems
Solid understanding of deep learning architectures (Transformers, SSMs, MoE,)
Experience with systems where hardware constraints matter: GPU programming, memory hierarchy, networking, or distributed computing
Strong software engineering fundamentals: clean design, extensibility, testability. Good judgment about when complexity is warranted
Effective communicator who works well across teams and time zones
Experience optimizing deep learning workloads on our GPUs using roofline models, Nsight/PyTorch profilers and end-to-end traces
Ways to stand out from the crowd:
Contributions to open-source inference runtimes and libraries - vLLM, SGLang, FlashInfer, Dynamo or similar
Hands-on work with LLM quantization (FP8, NVFP4, MXFP8, mixed-precision) and practical understanding of numerical precision tradeoffs
Track record with distributed inference at scale: tensor parallelism, pipeline parallelism, expert parallelism, disaggregation, multi-node orchestration
Deep knowledge of the latest LLM architectural trends: multi-token predictors, sparse hybrid models, attention and state-space mechanisms
Experience with performance modeling and simulation-to-silicon correlation.
B.Sc., M.Sc., or equivalent experience in Computer Science or Computer Engineering
5+ years of hands-on software engineering experience in performance-critical systems
Solid understanding of deep learning architectures (Transformers, SSMs, MoE,)
Experience with systems where hardware constraints matter: GPU programming, memory hierarchy, networking, or distributed computing
Strong software engineering fundamentals: clean design, extensibility, testability. Good judgment about when complexity is warranted
Effective communicator who works well across teams and time zones
Experience optimizing deep learning workloads on our GPUs using roofline models, Nsight/PyTorch profilers and end-to-end traces
Ways to stand out from the crowd:
Contributions to open-source inference runtimes and libraries - vLLM, SGLang, FlashInfer, Dynamo or similar
Hands-on work with LLM quantization (FP8, NVFP4, MXFP8, mixed-precision) and practical understanding of numerical precision tradeoffs
Track record with distributed inference at scale: tensor parallelism, pipeline parallelism, expert parallelism, disaggregation, multi-node orchestration
Deep knowledge of the latest LLM architectural trends: multi-token predictors, sparse hybrid models, attention and state-space mechanisms
Experience with performance modeling and simulation-to-silicon correlation.
This position is open to all candidates.
במקום לעבור לבד על אלפי מודעות, Jobify מנתחת את קורות החיים שלך ומציגה לך רק משרות שבאמת מתאימות לך.
מעל 80,000 משרות • 4,000 חדשות ביום
חינם. בלי פרסומות. בלי אותיות קטנות.
תל אביב - יפו
