Machine Learning Engineer (Sound Detection)

• Design and develop audio-based detection and classification systems for challenging real-world environments
• Implement robust signal processing pipelines tailored for noisy outdoor conditions
• Build and optimize machine learning models for sound event detection
• Develop low-latency high-reliability streaming pipelines
• Handle imbalanced and imperfect datasets using augmentation and synthetic data techniques
• Deploy and optimize models on edge hardware platforms (Jetson Raspberry Pi etc.)
• Optimize inference performance using ONNX TensorRT and OpenVINO
• Develop production-grade Python systems with modular architecture and multiprocessing capabilities
• Ensure system robustness under variable acoustic conditions and hardware constraints
• Collaborate with ML hardware and systems engineering teams to deliver integrated solutions

Qualifications :

• 4 years in ML / Audio / DSP / Edge AI
• Strong knowledge of audio signal processing (spectrograms noise reduction feature extraction)
• Experience working with noisy environments (wind city nature)
• Hands-on experience with ML for audio (CNNs YAMnet ONNX)
• Proficiency in training on imbalanced datasets and applying augmentation techniques
• Ability to build low-latency streaming pipelines for real-time audio processing
• Experience deploying models on edge devices (Raspberry Pi Jetson Nano)
• Optimization skills using ONNX TensorRT OpenVINO
• Production-level Python engineering experience (clean architecture multiprocessing modular pipelines)
• Proven track record of production deployment in real-world scenarios
• Professional proficiency in English

WILL BE A PLUS

• Acoustic domain knowledge (drone frequency ranges Doppler effect microphone arrays)
• Sensor fusion experience (audio video audio RF detection)
• Hardware integration skills (GPIO signal triggering)

Additional Information :

PERSONAL PROFILE

• High level of ownership and problem-solving mindset
• Ability to work across R&D engineering and hardware constraints
• Comfortable with real-world non-ideal data
• Strong collaboration skills in cross-functional teams

Remote Work :

No

Employment Type :

Full-time