LLM application engineer
1 month ago
We are seeking a Senior Natural Language Processing (NLP) Engineer with a robust background in developing multilingual voice bots and chatbots. The ideal candidate will possess knowledge of pretraining and continual pretraining of large language models (LLMs) for multiple languages. Expertise in fine-tuning LLMs using Parameter Efficient Fine-Tuning (PEFT) techniques, including Low-Rank Adaptation (LoRA), is also required. Additionally, experience with serving mechanisms such as VLLM and Sglang, along with familiarity with vector databases, LLamaIndex, CrewAI, Langchain, and Langsmith, is essential.
Responsibilities
Develop Multilingual Voice and Chatbot Solutions : Design and implement intelligent voice bots and chatbots that leverage advanced NLP techniques to enhance user interaction across multiple languages.
Extend LLM Capabilities : Enhance existing LLMs to support multiple languages through effective training strategies and data augmentation.
Fine-Tune LLMs : Utilize PEFT methods, particularly LoRA, to efficiently fine-tune large language models for specific applications while minimizing computational costs.
Implement Retrieval-Augmented Generation (RAG) : Develop RAG systems that provide contextual information to enhance the performance of NLP applications in various languages.
Model Deployment : Implement serving mechanisms such as VLLM and Sglang to ensure scalable and efficient deployment of NLP models.
Utilize Vector Databases : Leverage vector databases for efficient storage and retrieval of embeddings to improve model performance.
Collaborate with Cross-Functional Teams : Work closely with product managers, data scientists, and software engineers to integrate NLP solutions into existing platforms.
Research and Innovation : Stay updated on the latest advancements in NLP, voice technologies, and machine learning to continually improve our applications.
Requirements
Experience : Minimum of 5 years in NLP or related fields, with a focus on voice bot and chatbot development.
Technical Skills :
Proficiency in Python programming and experience with PyTorch.
Experience with huggingface, spacy, transformers and other NLP Libraries.
Strong understanding of LLM fine-tuning techniques, particularly PEFT and LoRA. Experience with vector databases, LLamaIndex, CrewAI, Langchain, and Langsmith.
Hands-on experience with RAG-based applications and LLM technologies.
Familiarity with serving mechanisms like VLLM and Sglang.
Proficiency in conversational AI technologies such as LLM function calling, information retrieval, vector databases, embedding models, and autonomous agents.
Skills in data preprocessing and ETL processes for training datasets.
Knowledge of ML algorithms and evaluation metrics.
Proficient in Git and experience with Agile project management tools.
CUDA Programming and Experience.
Docker and Kuberenetes.
Education : A degree in Computer Science, Data Science, Computational Linguistics, or a related field is preferred.
Analytical Skills : Strong problem-solving abilities with a focus on innovative solutions in NLP applications.
Communication Skills : Excellent verbal and written communication skills to effectively convey complex technical concepts.
Preferred Qualifications
Experience working with LLM and finetuning using DPO, PPO, PEFT.
Proven experience fine-tuning and adapting LLM for multiple languages.
If you are passionate about advancing the field of NLP through innovative voice technologies and model fine-tuning techniques across multiple languages, we invite you to apply and join our dynamic team
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