LLM Fine-Tuning Engineer
Role Summary
Optimize and fine-tune large language models (GPT-4o, Claude, Llama-3, etc.) for client-specific tasks in English, Arabic, Urdu, and Bengali.
Key Responsibilities
- Collect, clean, and annotate domain data sets.
- Design fine-tuning and reinforcement-learning-from-human-feedback (RLHF) pipelines.
- Benchmark model performance, latency, and cost.
- Package and deploy models via Azure ML or Amazon Bedrock.
Must-Have Qualifications
- 3+ years in NLP or ML engineering.
- Hands-on with Hugging Face Transformers, PEFT/LoRA, RLHF libraries.
- Strong Python and PyTorch.
- Experience with GPUs or distributed training (e.g., DeepSpeed).
Preferred
- Prior work on Arabic or South-Asian language models.
- MLOps exposure (Kubeflow, MLflow).
Engagement: Project-based, 20–40 hrs/week, remote.
Job Type: Full-time
Work Location: Remote
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