Machine Learning Engineer (Sound Detection)

TL;DR

Machine Learning Engineer (Edge AI): Designing and deploying real-time acoustic detection systems for complex and noisy environments with an accent on audio signal processing and edge device optimization. Focus on building low-latency streaming pipelines, implementing ML models for sound event detection, and optimizing inference using ONNX and TensorRT.

Location: Remote (Europe, Ukraine)

Company

hirify.global is a professional software engineering company operating across a wide variety of technology domains and businesses.

What you will do

• Design and develop audio-based detection and classification systems for challenging real-world outdoor environments.
• Implement robust signal processing pipelines tailored for noise reduction and feature extraction.
• Build and optimize machine learning models for sound event detection and low-latency streaming.
• Deploy and optimize models on edge hardware platforms such as Jetson and Raspberry Pi using ONNX, TensorRT, and OpenVINO.
• Develop production-grade Python systems utilizing modular architecture and multiprocessing.
• Collaborate with ML, hardware, and systems engineering teams to deliver integrated solutions.

Requirements

• 4+ years of experience in ML, Audio, DSP, or Edge AI.
• Strong knowledge of audio signal processing (spectrograms, noise reduction, feature extraction).
• Hands-on experience with ML for audio (CNNs, YAMnet, ONNX) and handling imbalanced datasets.
• Proven track record of deploying models on edge devices (Raspberry Pi, Jetson Nano).
• Production-level Python engineering experience with clean architecture and modular pipelines.
• Professional proficiency in English.

Nice to have

• Acoustic domain knowledge, including drone frequency ranges and the Doppler effect.
• Experience with sensor fusion (audio combined with video or RF detection).
• Hardware integration skills involving GPIO and signal triggering.

Culture & Benefits

• Remote work flexibility with the option to use outstanding offices.
• Flexible schedule and exposure to a wide variety of technology and business domains.
• Health and legal support for employees.
• Access to an active professional community and continuous education opportunities.
• Sports and community activities.