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, 2040 hrs/week, remote. Job Type: Full-time Work Location: On the road
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