Deep Learning Software Engineer

Tel Aviv · Full-time

About The Position

We’re looking for a deep learning software engineer who is versatile, curious, independent, and keen to embark on true challenges. As part of the Deci AI team, you will gain knowledge and industrial proficiency in a broad spectrum of advanced deep-learning frameworks. You will utilize cutting edge hardware and state-of-the-art models, all while acquiring software development best practices.

This job requires a thorough understanding of both software engineering principles and deep learning theory. You will participate in the development of Deci’s core products - enabling graph compilation, model deployment, and more - all aimed at hardware-aware inference acceleration.


  • Bachelor’s degree in CS/CE/EE or equivalent experience
  • 4+ years experience as a software engineer in a performance-critical production setting
  • Experience working with at least one major DL framework - PyTorch/Tensorflow
  • Experience working with OOP, design patterns, testing pyramids and SOLID software craftsmanship
  • Deep understanding of computer architecture concepts, hardware accelerators, and different compiler toolchains
  • Professional team player with excellent communication skills in verbal and written English

Preferred qualifications

  • Familiar with highly concurrent systems, GPU programming, CUDA and the CUDA Toolkit
  • Extensive experience deploying deep neural models to production settings - on cloud or edge devices
  • Track record of profile-based performance analysis, methodical discovery of bottlenecks, and general hardware utilization optimization
  • Familiar  with stream processing frameworks (GStreamer, ROS, …) and efficient data-management techniques that they leverage
  • Knowledge of common SOTA deep learning architectures, their pre and post processing data transformations, and the relevance of these transformations to different deep learning tasks
  • Deep understanding of Unix-based OS internals - from process and thread management to the virtual memory system and file systems


  • Develop the core logic behind Deci’s DL development platform. Contribute to inference libraries and internal model optimization tools used by Deci’s customers, researchers, and algorithm teams.
  • Develop strategies and infrastructure aimed at improving the reliability of Deci’s deep learning systems
  • Port Deci’s existing products to new industry-leading hardware platforms - from ASICs to powerful GPUs.
  • Develop and deliver production-ready inference pipelines that most effectively utilize available HW resources under customer-defined constraints
  • Adopt and integrate cutting-edge research - in the fields of model optimization and deployment - into Deci products and tools

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