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 collaboration.
- Proper time management.
- Highly autodidact, independent and proactive.
Responsibilities:
- Develop and optimize cutting-edge generative AI models, including large language models (LLMs) and multimodal systems, tailored for SpiNNcloud’s brain-inspired hardware.
- Actively participate in the planning and execution of scalable AI systems capable of end-to-end model training, tuning, and deployment.
- Design and implement high-performance AI frameworks and libraries with an emphasis on hardware-awareness and energy efficiency.
- Perform in-depth analysis of generative AI algorithms to identify opportunities for optimization in terms of accuracy, latency, and energy consumption.
- Collaborate with researchers and developers to prototype innovative tools and infrastructure for generative AI applications.
- Contribute to the development of robust APIs and coherent toolsets for seamless integration with SpiNNcloud’s infrastructure.
- Share impactful findings and results through GitHub repositories, scientific publications, and presentations.
- Contribute to the development and documentation of demonstrators.
Minimum Requirements:
- Advanced degree (PhD, MSc, or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields.
- Strong mathematical fundamentals and a deep understanding of machine learning algorithms, particularly in generative AI.
- Proficient programming skills in Python and experience with deep learning frameworks (e.g., PyTorch, JAX).
- Substantial experience in debugging, performance analysis, and software development best practices.
- Knowledge of distributed systems and familiarity with scaling AI training pipelines.
- Experience with Tiny Machine Learning.
Added value:
- Expertise in applying generative AI techniques to LLMs and multimodal models (e.g., image, video, or speech).
- Hands-on experience with deployment environments and tools like ONNX, Triton, or TensorRT.
- Familiarity with CPU/GPU architectures and energy-efficient computing techniques.
- Experience working with neuromorphic or event-based hardware systems (e.g., SpiNNaker).
- Proven track record of contributing to open-source projects or publications in top-tier conferences.
- Strong understanding of performance optimization for AI algorithms in hardware-constrained environments.
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
