Job Details

International product IT project is looking for an ML engineer to work on the AMD system. Starting from $3500 to $5000. Hybrid format with subsequent full remote work.

We are a product team creating an intelligent cloud telephony ecosystem for the US and Canadian markets. Our product is a fault-tolerant platform with millions of traffic turnovers. ML here is not a supporting feature, but the foundation of the system, operating in real-time. We are looking for an engineer who thoroughly understands the internal architecture of audio models and is ready to be responsible for their operation in a high-load production environment. Responsibilities: - Development of the AMD (Answering Machine Detection) system: retraining and tuning models for real-time call classification (distinguishing humans from answering machines/IVR). - Full-cycle development: from collecting and "dirty" labeling of audio data to deploying and calibrating thresholds in production. - Integration into the Core product: transferring ML components into the backend infrastructure (C# / SIP / RTP stack) via ONNX Runtime. - Latency optimization: fighting for milliseconds in audio streaming conditions. - Deep Analysis: identifying errors and analyzing complex edge cases in real call scenarios. - Research (R&D): experiments with noise reduction, VAD, and new speech processing architectures.

We expect: - 2+ years of experience in ML in production (when your model actually worked with users). - Practical experience with Speech/Audio: understanding how audio features and modern sound processing architectures work. - Engineering approach (QA-mindset): you are genuinely interested in "digging" into data anomalies and testing the system's resilience. - Understanding of classics and modern approaches: Fine-tuning, Transfer Learning, and the ability to work with metrics (Precision/Recall, ROC-AUC, Calibration). - Ability to work end-to-end: from raw files to optimized inference. What's important: - Engineering autonomy: we value those who find problems themselves and bring solutions to production. - Background: we highly welcome candidates who came to ML from Backend or QA; we value code and testing culture. - Readiness for dynamics: the project is growing, there are many tasks, and they directly impact the business. Will be a plus: - Experience in Speech/Audio domain (ASR, VAD, Audio Classification). - Understanding of VoIP specifics and data streaming. - Experience with MLOps and model monitoring tools.

Conditions: - Mandatory offline onboarding in Tashkent (2-3 months) for product immersion, followed by full remote work. - Real production tasks in an international product with high load. - Opportunity for professional growth and compensation review as tasks become more complex. - Work in a team with strong engineering expertise and no bureaucracy.