Algorithm Engineer

A breakthrough, commercially validated Medical Device and Advanced Wearables technology company, operating as an autonomous, high-caliber Israeli R&D center backed by one of the world’s largest global healthcare and consumer conglomerates.

Employing dozens of professionals locally, the organization combines the robust stability, resources, and career resilience of a global market leader with the agile, collaborative, and fast-paced environment of an elite startup.

The development center is located in Tel Aviv, operating on a hybrid model with two days working from home.

Role Description-

• Serving as a Senior Audio & Speech AI Algorithm Engineer, taking end-to-end algorithmic ownership within the core AI research squad, driving deep learning speech and audio solutions from exploratory research and PoC to production deployment on constrained wearable edge devices.
• Researching, designing, and implementing cutting-edge Deep Learning and Classical Signal Processing architectures, including Speech Enhancement, Acoustic Feedback Cancellation (AFC), Neural Beamforming, and Acoustic Scene Recognition/Classification.
• Developing, training, and benchmarking complex deep neural network models using Python (PyTorch / TensorFlow) on extensive real-world acoustic datasets.
• Leading comprehensive Model Optimization, Quantization, and Pruning to enable real-time inference under strict edge constraints (ultra-low latency, low power consumption, minimal memory footprint, and tight compute budgets on embedded DSP / NPU architectures).
• Building robust algorithmic evaluation frameworks, automated training pipelines, and objective audio quality benchmarking suites.
• Collaborating cross-functionally with Embedded Firmware, System Architecture, and Hardware teams to integrate and validate high-fidelity audio algorithms on proprietary edge hardware.

Requirements-

• M.Sc. or Ph.D. in Electrical Engineering, Computer Science, Data Science, or a closely related technical discipline (open to exceptional candidates with a B.Sc. and extensive, proven algorithmic track record) – Mandatory
• 5 years of hands-on algorithmic experience bridging Deep Learning / AI and Audio Signal Processing (DSP) – Mandatory
• Proven, direct experience developing and deploying machine learning models specifically for Audio, Speech, or Acoustic applications – Mandatory
• Advanced, hands-on programming depth in Python and modern deep learning frameworks (PyTorch or TensorFlow) – Mandatory
• Strong mathematical and theoretical grasp of audio engineering fundamentals: spectral analysis, spatial audio, microphone arrays, beamforming, and noise suppression – Mandatory
• Autonomous problem solver with a strong research-to-production mindset and fluent English communication skills – Mandatory

Advantages & Nice to Have

• Proven track record in Edge AI optimization (quantization-aware training, INT8/FP8 quantization, pruning, deployment on DSPs, NPUs, or microcontrollers) – Significant Advantage
• Prior industry background in Medical Devices, Hearing Technologies, or Smart Audio/Acoustic Wearables – Significant Advantage
• Hands-on experience with C/C implementation, fixed-point arithmetic, or low-level DSP programming – Advantage

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