Adapt NVIDIA PersonaPlex-7B-v1 for Russian, Uzbek
Budget: $250 – $750 USD
Title
Senior ML Engineer – Fine-tuning NVIDIA PersonaPlex (Helium) for Russian and Uzbek
Project Description
We are building a real-time voice AI assistant based on NVIDIA PersonaPlex-7B-v1.
The model currently works in English.
Our goal is to adapt it for Russian and Uzbek and integrate it into a voice assistant platform.
We already have prepared datasets.
We are looking for an experienced Speech / LLM engineer who has worked with multimodal models and LoRA fine-tuning.
---
Main Tasks
1. Fine-tune NVIDIA PersonaPlex-7B-v1 for Russian and Uzbek language support
2. Train LoRA adapters for multilingual capability
3. Adapt the speech-to-speech pipeline (audio tokens + Helium backbone)
4. Integrate persona conditioning for our voice assistant
5. Optimize inference for real-time interaction
---
Model Architecture
Base model:
NVIDIA PersonaPlex-7B-v1
(Moshi architecture + Helium backbone)
Speech-to-speech conversational AI with full-duplex interaction.
---
Dataset
Prepared datasets include:
• Russian conversation dataset
• Uzbek conversation dataset
• Persona dialogue dataset
Estimated size: ~300k–500k samples.
---
Technical Requirements
Strong experience with:
• PyTorch
• HuggingFace Transformers
• LoRA / QLoRA / PEFT
• Multilingual model fine-tuning
• Speech models or audio token models
Experience with one of the following is highly preferred:
• Whisper
• NeMo
• wav2vec
• multimodal LLMs
---
Infrastructure
Training environment:
• A100 / H100 GPUsor other
• Docker environment
---
Expected Deliverables
• LoRA adapters for RU and UZ
• Training scripts
• Evaluation results
• Integration instructions
---
Project Timeline
Estimated implementation time:
3–7 days.
---
When applying please include
• examples of LLM fine-tuning projects
• experience with speech models
• experience with LoRA training
Senior ML Engineer – Fine-tuning NVIDIA PersonaPlex (Helium) for Russian and Uzbek
Project Description
We are building a real-time voice AI assistant based on NVIDIA PersonaPlex-7B-v1.
The model currently works in English.
Our goal is to adapt it for Russian and Uzbek and integrate it into a voice assistant platform.
We already have prepared datasets.
We are looking for an experienced Speech / LLM engineer who has worked with multimodal models and LoRA fine-tuning.
---
Main Tasks
1. Fine-tune NVIDIA PersonaPlex-7B-v1 for Russian and Uzbek language support
2. Train LoRA adapters for multilingual capability
3. Adapt the speech-to-speech pipeline (audio tokens + Helium backbone)
4. Integrate persona conditioning for our voice assistant
5. Optimize inference for real-time interaction
---
Model Architecture
Base model:
NVIDIA PersonaPlex-7B-v1
(Moshi architecture + Helium backbone)
Speech-to-speech conversational AI with full-duplex interaction.
---
Dataset
Prepared datasets include:
• Russian conversation dataset
• Uzbek conversation dataset
• Persona dialogue dataset
Estimated size: ~300k–500k samples.
---
Technical Requirements
Strong experience with:
• PyTorch
• HuggingFace Transformers
• LoRA / QLoRA / PEFT
• Multilingual model fine-tuning
• Speech models or audio token models
Experience with one of the following is highly preferred:
• Whisper
• NeMo
• wav2vec
• multimodal LLMs
---
Infrastructure
Training environment:
• A100 / H100 GPUsor other
• Docker environment
---
Expected Deliverables
• LoRA adapters for RU and UZ
• Training scripts
• Evaluation results
• Integration instructions
---
Project Timeline
Estimated implementation time:
3–7 days.
---
When applying please include
• examples of LLM fine-tuning projects
• experience with speech models
• experience with LoRA training