As a deep-tech startup, we are looking for talented and passionate people with an appetite for problem solving. 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
Responsibilities:
- 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.
Minimum Requirements:
- 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
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.
Your contact: Hector Andres Gonzalez Diaz
Location: SpiNNcloud Systems GmbH, Freiberger Straße 37, 01067 Dresden
