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1 day ago
We are seeking an experienced Large Language Model Engineer to develop and deploy cutting-edge natural language processing models.
Key Responsibilities:
- Design, train, and fine-tune large-scale deep learning models using GPT, LLaMA, BERT, T5, etc.
- Optimize model performance through techniques such as quantization, pruning, LoRA, and distillation.
- Implement retrieval-augmented generation (RAG) and vector search solutions (FAISS, Pinecone).
- Deploy models using TorchServe, Triton, and Hugging Face Inference Endpoints.
- Maintain efficient MLOps practices, including monitoring and versioning.
To be successful in this role, you will need:
- 4+ years of experience in NLP, deep learning, and model training.
- A degree in Computer Science, Machine Learning, or a related field.
- Proficiency in Python, PyTorch, TensorFlow, or JAX.
- Experience with distributed training using Ray, DeepSpeed, FSDP.
- Strong knowledge of ML frameworks, vector databases, and MLOps tools.
The following qualifications would be beneficial:
- Experience with multi-modal models (text + image/audio).
- Understanding of secure AI deployment in regulated industries.
- Contributions to open-source NLP projects.
The ideal candidate will have experience with the following technologies:
LLM Training: Hugging Face, OpenAI, DeepSpeed, LoRA
ML Frameworks: PyTorch, TensorFlow, JAX
Vector Search: FAISS, Pinecone, Weaviate
Deployment: MLflow, Kubernetes, Docker
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