Description

SpiNNcloud Systems is a deep tech spin-off from the Chair of Highly-parallel VLSI Systems and Neuro-microelectronics at the Technische Universität Dresden. We provide highly-parallel and real-time computing capabilities to empower our customers with the third generation of AI-driven systems. Our unique combination of statistical AI and brain-like computing advances real-time AI applications to an unprecedented large-scale and with an extremely high energy efficiency.

As a deep-tech startup, we are looking for talented and passionate people with an appetite for problem solving.

  • Implementation of state-of-the-art Spiking Neural Networks in CUDA-based frameworks for GPUs (e.g., NENGO, GeNN) and custom SpiNNcloud hardware.
  • Adapt traditional algorithms and computational models to function effectively on neuromorphic hardware.
  • Development of Neuromorphic software and standards.
  • Optimization and benchmark of a wide variety of applications and mathematical models to push the boundaries of neuromorphic hardware and software.
  • Design, development, testing, deployment, maintenance, and enhancement of software interacting in real-time with sensors and actuators.
  • Development of large-scale neuromorphic models at a supercomputer scale.
  • Technical documentation of the results and exploration process across experiments, and across detailed literature studies.

Besides the minimal requirements for this job position, your profile is a good fit to our company if you have the following values:

  • High flexibility and adaptability
  • Tranquility to work under pressure
  • Appetite for learning and problem solving
  • Critical thinking
  • Ability to communicate effectively
  • Keen to collaborate with external partners
  • Proper time management
  • Highly autodidact, independent and proactive
  • BSc, MSc, or Dipl.-Ing. in Computer Science, Electrical Engineering, Computer Engineering, Physics, Mathematical sciences, or any other related computationally intensive field.
  • Strong understanding of neuromorphic computing principles and architectures.
  • Proficiency in programming with Python and C.
  • Experience with modern Neuromorphic (e.g., Lava, sPyNNaker, snntorch, norse, spyx or PyNN) or Machine Learning frameworks (e.g., Spark ML, Huggingface, TensorFlow or PyTorch).
  • Familiarity with techniques such as surrogate gradients, spike-timing-dependent plasticity (STDP), and other methods specific to SNN training for various applications.
  • Experience developing and optimizing either Machine Learning models, Neuromorphic models, or applications in DSPs, GPUs (CUDA-based), high performance computing clusters, or low-level compilers.
  • Solid knowledge of virtualization and containerization (Docker).
  • High flexibility and adaptability in a demanding and constantly changing field such as Artificial Intelligence.

Added value:

  • Dr.-Ing., or PhD in Computer Science, Electrical Engineering, Computer Engineering, Physics, Mathematical sciences, or any other related computationally intensive field
  • Hands-on experience using neuromorphic hardware (e.g., SpiNNaker, Intel Loihi, IBM TrueNorth, etc.)
  • Participation in research papers related to neuromorphic computing or machine learning
  • Experience deploying Machine Learning or Neuromorphic models at a large scale
  • Solid understanding of Symbolic architectures.
  • Familiarity with combinatorial optimization algorithms.
  • Strong mathematical background.
  • Being an active contributor in Github or any other hosting software development with version control

  • Dresden
  • Veröffentlicht vor 5 Stunden

We offer a highly competitive salary with reallocation benefits in a flexible and inclusive work environment. We are an equal opportunity employer, and hence we welcome people of different backgrounds, nationalities and experiences.