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

Originally posted on Himalayas