نشان کن
کد آگهی: KP8573798121
استخدام Enterprise Audio AI Platform) Machine Learning Specialist)
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خانه هوش ایران | Iran Ai House
در تهران
اطلاعات شغل:
نوع همکاری: تماموقت
مدرک تحصیلی مورد نیاز: کارشناسی - فوقلیسانس
مهارتهای مورد نیاز:
وب
برنامه نویسی وب
پرداختها: توافقی
متن کامل آگهی:
(ASR, TTS, Multimodal LLM Systems)
## Position Summary
We are seeking an experienced *Machine Learning Specialist to lead the design, and development of enterprise-grade audio AI solutions, including Automatic Speech Recognition (ASR), Text-to-Speech (TTS), and Large Language Models with audio modality.
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## Key Responsibilities
### Speech Recognition (ASR)
Architect and maintain production ASR systems based on state-of-the-art frameworks such as:
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## Key Responsibilities
### Speech Recognition (ASR)
Architect and maintain production ASR systems based on state-of-the-art frameworks such as:
OpenAI Whisper
Meta AI wav2vec 2.0
Meta AI wav2vec 2.0
Conformer-based architectures from Google Research
Lead multilingual and domain-adapted fine-tuning initiatives.
Lead multilingual and domain-adapted fine-tuning initiatives.
Implement streaming, low-latency, and high-availability ASR services.
Define enterprise evaluation benchmarks (WER, latency SLAs, robustness).
Define enterprise evaluation benchmarks (WER, latency SLAs, robustness).
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### Enterprise Text-to-Speech (TTS)
Design scalable neural TTS systems leveraging technologies inspired by:
Google Tacotron
Google Tacotron
NVIDIA FastPitch
Microsoft VALL-E
Microsoft VALL-E
Ensure compliance with voice safety, identity protection, and brand voice policies.
Optimize inference pipelines for GPU clusters and edge devices.
Optimize inference pipelines for GPU clusters and edge devices.
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### Multimodal & Audio-Enabled LLM Systems
Integrate ASR and TTS pipelines with enterprise LLM ecosystems, including:
OpenAI GPT-based systems
OpenAI GPT-based systems
Meta LLaMA variants
Design speech-to-speech conversational platforms.
Design speech-to-speech conversational platforms.
Develop cross-modal embedding alignment strategies.
Implement guardrails, safety filters, and compliance monitoring.
Implement guardrails, safety filters, and compliance monitoring.
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### Architecture & Infrastructure
Deploy models using containerized environments (Docker, Kubernetes).
Implement MLOps best practices (CI/CD, monitoring, drift detection).
Implement MLOps best practices (CI/CD, monitoring, drift detection).
Collaborate with DevOps, Security, Legal, and Data Governance teams.
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## Required Qualifications
MSc or PhD in Computer Science, Machine Learning, Electrical Engineering, or related field.
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## Required Qualifications
MSc or PhD in Computer Science, Machine Learning, Electrical Engineering, or related field.
5+ years of experience in ML engineering or speech AI.
Strong expertise in:
Strong expertise in:
Transformer-based architectures
Speech signal processing
Speech signal processing
PyTorch / TensorFlow
Distributed training and inference
Distributed training and inference
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## Preferred Qualifications
Familiarity with HPC & CUDA programming.
Experience with real-time streaming architectures.
Experience with real-time streaming architectures.
Publications or patents in speech or multimodal AI.
Knowledge of model quantization and hardware optimization.
Knowledge of model quantization and hardware optimization.
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