Neuromorphic Engineer

SpiNNcloud Systems GmbH; Dresden; Vor Ort; EUR 60.000 - 100.000; Vollzeit

Zusammenfassung

Ein innovatives Deep-Tech-Startup sucht talentierte und leidenschaftliche Fachkräfte, die bereit sind, sich den Herausforderungen der neuromorphen Berechnung zu stellen. In dieser spannenden Rolle sind Sie für die Implementierung von Spiking Neural Networks in CUDA-basierten Frameworks verantwortlich und tragen zur Entwicklung neuromorpher Software und Standards bei. Sie werden die Möglichkeit haben, an der Spitze der Technologie zu arbeiten und Ihre Fähigkeiten in einem dynamischen Umfeld weiterzuentwickeln. Wenn Sie eine Leidenschaft für Problemlösungen und eine starke Neugier für neue Technologien haben, könnte dies die perfekte Gelegenheit für Sie sein.

Qualifikationen

• Starkes Verständnis für neuromorphe Rechenprinzipien und Architekturen.
• Erfahrung in der Programmierung mit Python und C.

Aufgaben

• Implementierung von Spiking Neural Networks in CUDA-basierten Frameworks.
• Entwicklung von neuromorphen Software-Standards und Optimierung von Anwendungen.

Kenntnisse

Problem Solving

Flexibility

Critical Thinking

Effective Communication

Time Management

Self-Directed Learning

Ausbildung

BSc, MSc, or Dipl.-Ing. in Computer Science

PhD in related field

Tools

CUDA

Docker

NENGO

GeNN

Lava

PyTorch

TensorFlow

Jobbeschreibung

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:

1. High flexibility and adaptability
2. Tranquility to work under pressure
3. Appetite for learning and problem solving
4. Critical thinking
5. Ability to communicate effectively
6. Keen to collaborate with external partners
7. Proper time management
8. 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