Embedded Machine Learning Engineer

Das ist der Job

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

Darum lohnt es sich

We offer a highly competitive salary with reallocation benefits in a flexible and inclusive work environment. 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: Actively participate in the planning and execution of the development of the Embedded Software in the 10 Million cores SpiNNcloud Machine.

Explore energy and performance driven optimizations to machine learning algorithms. Develop hardware-aware optimizations for cutting edge ML algorithms. Build a robust and consistent compiler infrastructure for SpiNNcloud hardware.

Design and implementation of benchmarks involving different metrics (e.g., Latency, Energy Efficiency, Energy-delay product, etc.). Contribute to the development and documentation of cool demonstrators. Minimum Requirements: Experience with Tiny Machine Learning.

Strong programming skills and substantial development experience in Python, and C, involving data structures, graphs, and object-oriented programming. Solid understanding of Machine Learning algorithms. Experience with embedded systems involving multicore environments and sensors.

Required expertise in development tools (e.g., git or svn) for revision control. BSc, MSc or Dipl.-Ing. in Computer Science, Electrical Engineering, Computer Engineering, or any other related computationally intensive field. Added value: Active contributor in Github or any other hosting for software development with version control.

Experience with DevOps and continuous integration & delivery tools (e.g., Gitlab). Understanding of Event-based Machine Learning or Neuromorphic algorithms. Experience working with Neuromorphic hardware (e.g., Loihi or SpiNNaker).

Dr.-Ing., or PhD in Computer Science, Electrical Engineering, Computer Engineering, Physics, Mathematical sciences, or any other related computationally intensive field. Experience developing Computer vision applications with real-time sensor streams.

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