המקום בו המומחים והחברות הטובות ביותר נפגשים
Job DescriptionClassical Machine learning is the go-to solution in tabular data, it works with relatively small amounts of train datasets and has inherent explainability. Along with lower computational requirements it gets strong demand across multiple domains. Python has become #1 language for data science, and it is still lacking the performance and efficiency of native languages. You will be playing critical role in changing that by helping data science to scale beyond laptop to powerful servers and clusters.As a part of the team, you will be working on bringing full potential of the latest Intel CPUs and GPUs to the Python and classical Machine Learning ecosystems. With efficient backend in C++ and ability to seamlessly integrate into the existing Python data science codes, our tools unleash orders of magnitude speedups for performance critical data science operations.Responsibilities:
You will be working in a product team performing design, implementation, testing, code review, and creating documentation.
You will cooperate with other teams on other components related issues.
Minimum Qualifications:
2+ years of experience developing production code in C/C++ and Python
Proven strong mathematical/stat background
Knowledge in Machine Learning area
Knowledge in computer since algorithms
Git + GitHub
Additional Qualifications:
Experience with parallelism in shared (Intel TBB, OpenMP) and distributed memory (MPI, SHMEM, Apache Spark, Dask)
Knowledge of Numpy/Scipy, Pandas, Scikit-Learn, Numba internals
Experience with Conda Pip environments
Experience in performance optimization of numerical applications
Scripting languages (shell is preferred)
Experience with SYCL
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