Lead/manager Ai Optimizations

hace 2 meses


Barcelona, España Esperanto.ai A tiempo completo

Esperanto is creating a new generation of Artificial Intelligence processing solutions delivering unmatched energy efficiency (performance/watt), scalability, and flexibility. The historical limitations on many-core designs have always been complexity and power consumption, but it is now possible to create designs with over a thousand processor cores on one piece of silicon. Esperanto’s no-compromise solution breaks through previous barriers in delivering a massively parallel and flexible processor that combines high performance with ultra-low power consumption. Our high-performance ET-MaxionTM core is designed to deliver the best single-thread RISC-V performance. Our ET-MinionTM core compute array is designed for energy efficiency, delivering TeraFlops and TeraOps of computing.

**About the Role**

**What you will do**
- Define, plan, and lead the work on software optimizations for transformer models
- Develop software-driven optimizations targeting a novel RISC-V architecture
- Implement algorithmic and compiler solutions for our high-performance HW accelerators
- Integrate different inter-operator optimizations in the whole SW stack
- Analyze and characterize the efficiency of the SW optimizations
- Interact with functional and performance simulators

**Minimum Qualifications**
- MS in Computer Science or a related technical field
- Good understanding of object-oriented programming
- Knowledge of parallel programming
- Knowledge of algorithmic complexity, data structures, and graph algorithms
- Seasoned experience in C++ and Python
- Working experience in Linux distributions
- Business fluent English
- This is a hybrid position located in Barcelona

**Valuable Qualifications**
- Knowledge of recent C++ extensions (C++14, C++17, C++20)
- Experience in Pytorch and ONNX Runtime
- Knowledge of kernel vectorization
- Experience with basic GitLab-CI or related CI pipeline flows
- Knowledge of unittest libraries (gtest, pytest)
- Experience in ML compiler development
- Knowledge in high-performance computing
- Knowledge of processor and SOC architecture
- Knowledge of AI/ML algorithms and Neural Networks (CNNs, recommending systems, transformers, LLMs, VLMs, stable diffusion, whisper)



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