Key Duties/Responsibilities: 

• Selection, adaptation, and fine-tuning of models for signal and speech processing (including CNN/Transformer architectures, state-space models, and end-to-end ASR).
• Optimizing inference: quantization, pruning, kernel fusion, batching strategies, mixed precision, TorchScript/torch.compile, export to ONNX/TensorRT.
• Implementing high-performance inference paths in PyTorch and LibTorch (PyTorch C++).
• Deployment and operation of models in the NVIDIA Triton Inference Server—including model repository, ensembles, business logic scripting, dynamic batching, and custom backends.
• Building processing chains around the models: signal preprocessing, feature extraction, streaming pipelines, pre-/post-processing.
• Taking prototypes from development to market readiness: benchmarking, profiling, test coverage, reproducibility, monitoring, and versioning of models.
• Close collaboration with system architecture and product management.
• Evaluating new methods and tools for their practical suitability for our performance goals.

Key Skills/Experience: 

• BSc/MSc in one of the following fields, Computer Science, Electrical Engineering, Physics, Mathematics, or a comparable qualification—or equivalent practical experience.
• Several years of experience with PyTorch beyond training: You know where models slowdown in production and how to fix it.
• Solid knowledge of C++ (C++17 or later) and experience with the PyTorch C++ API.
• Practical experience with Triton Inference Server.
• In-depth knowledge of digital signal processing (FFT, filter design, modulation, spectrogram representations) or speech processing (ASR, speaker embeddings, speech enhancement).
• Experience with profiling and GPU optimization (CUDA fundamentals).
• Proficiency with Linux, Git, Docker, and CI/CD.
• Fluent in spoken and written English.

Nice to Have: 

• Experience with CUDA kernel development or custom Triton backends.
• Experience working with SDR hardware and real-world RF datasets.
• Experience with edge deployment (Jetson, embedded GPUs) and models operating under tight resource constraints.

Key Benefits: 

• Attractive remuneration package.
• Private health insurance.
• Provident fund.
• Gym membership.
• Hybrid working scheme.
• Continuous personal development scheme.

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