Neuromorphic Engineer

Direct message the job poster from SpiNNcloud Systems

Co-Founder & co-CEO @ SpiNNcloud, provider of the world’s largest brain-like supercomputer | PhD in chip design

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
• 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.

Seniority level

Entry level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

Computer Hardware Manufacturing

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