AI / ML Engineer – Hardware-Aware & Neuromorphic Systems

We are looking for an experienced AI / Machine Learning Engineer who will help us develop and adapt neural network models for novel hardware architectures, including memristor-based and neuromorphic systems.

The role sits at the intersection of machine learning, hardware-aware AI optimization and emerging computing paradigms. 

It is not suitable for candidates focused purely on software-based machine learning.
We are specifically looking for engineers interested in the intersection of AI and hardware.

​You will actively co-design AI models together with hardware engineers, considering physical constraints of the target architecture (latency, memory, energy, device behavior).​

This role focuses on core machine learning and hardware-aware AI research, not on building applications around existing AI APIs or prompt-engineering workflows.

What you will work on

• Development, training and evaluation of neural network models for research and applied projects
• Adaptation and optimization of AI models for non-standard hardware architectures
• Exploration of neuromorphic computing approaches and spiking neural networks
• Cooperation with hardware teams working on memristor-based devices and in-memory computing
• Implementation and evaluation of ML workloads on GPU/CUDA platforms
• Experimentation with new AI paradigms relevant for low-power and hardware-efficient AI
• Preparation of technical materials for international research projects (IPCEI, Horizon Europe)
• Internal knowledge sharing and mentoring of colleagues

Required skills and experience

• Strong background in machine learning and neural networks
• Practical experience with training and optimization of ML/DL models
• Solid understanding of linear algebra, probability, statistics and optimization
• Experience with PyTorch or TensorFlow
• Strong programming skills in Python
• Experience with GPU computing (CUDA or similar) and understanding of AI workloads on modern hardware
• Ability to analyze model performance and optimize training and inference
• Understanding of hardware constraints in AI (memory, latency, energy)
• Experience with hardware-aware model optimization OR low-level ML deployment
• Basic understanding of computer architecture or electronic systems

Highly desirable

• Experience with hardware-aware machine learning
• Knowledge of neuromorphic computing
• Experience with spiking neural networks
• Understanding of memristive devices or in-memory computing concepts
• Experience with C++ or other low-level programming languages
• Experience collaborating with hardware or semiconductor teams
• Research background (PhD or equivalent experience)

• Opportunity to work on next-generation AI hardware concepts
• Collaboration with international research teams
• Participation in European research projects (IPCEI, Horizon Europe)
• Small team where you can influence the direction of research and development
• Modern and comfortable work environment with an informal company culture.
• Flexibility to work both onsite and offsite, depending on your preference and project requirements
  
• Company-wide events and regular team breakfasts.
• Multisport card.
• A meal allowance of €5.30 and the option to dine in the company canteen for €6.
• A contribution for work and life anniversaries ranging from €50 to €300.
• Referral program – a bonus of up to €500 for successful referrals.
• A motivating annual reward for good company performance.
• Single-shift operations and flexible working hours.
• Free parking on-site.
• If needed, accommodation on-site at discounted rates.