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Homeoffice AI Software Engineer

Rivos Inc.  ·  nan, Estados Unidos de América · Remote

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About the job

Open position for AI Software development at a fast-moving startup.

Potential Responsibilities

  • Build-up components of an AI Software Stack
  • Port AI Software to run on a new H/W platform
  • Profiling and tuning of AI applications
  • Implement math operators used in AI
  • Build up infrastructure to validate AI models running on a new H/W platform


Requirements

  • Coursework or experience with C or C++
  • Coursework or experience in Operating Systems or Embedded Software Engineering
  • Coursework or experience with Assembly Language Programming and Computer Architecture
  • Familiarity with Python
  • Excellent skills in problem solving, written and verbal communication
  • Strong organization skills, and highly self-motivated.
  • Ability to work well in a team and be productive under aggressive schedules.
  • Desire to learn new skills and attack novel problems


Optional Requirements

  • Experience with NumPy, PyTorch, TensorFlow or JAX
  • Experience with Rust
  • Experience with CUDA, OpenCL, OpenGL, or SYCL
  • Coursework or experience with compiler development
  • Coursework or experience with Machine Learning algorithms


Education And Experience

  • Bachelor’s, Master’s, or PhD in Computer Engineering, Software Engineering or Computer Science


About Rivos

Founded in May 2021, Rivos has assembled a world class team of silicon, software and platform designers. The company is backed by premier financial and strategic investors who share its long term vision of building industry-leading power efficient, high performance, secure server solutions based on RISC-V.

Rivos supports the intense requirements of the large language models and data analytics that will remake the enterprise, by providing the full solution of optimized chips combining RISC-V CPUs and a Data Parallel Accelerator, a reference multi-chip OCP modular server, and a full firmware-to-application open software stack. Customer workloads are easily deployed using their existing models giving an immediate TCO benefit.

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