Job Summary
We are seeking for AI/ML Engineer with expertise in fine-tuning and deploying Large Language Models (LLMs) and Vision-Language Models (VLMs). The ideal candidate will be experienced in optimizing models using techniques such as LoRA, implementing Retrieval-Augmented Generation (RAG) systems, and developing scalable AI pipelines for diverse applications including text summarization, object detection, and intelligent agents.
Key Responsibilities
- Fine-tune and optimize LLMs/VLMs (e.g., LoRA or other low-rank approaches) to meet project needs, delivering to use-cases such as intent recognition, text summarization, multi-turn dialogue, object detection, image captioning, and more.
- Design and implement Retrieval-Augmented Generation (RAG) systems.
- Build and maintain the toolchain for fine-tuning and deploying LLMs/VLMs manage training clusters and deliver efficient inference on both server-side and embedded targets.
- Apply prompt-engineering and agent-based techniques to design, evaluate, and iterate solutions tailored to user scenarios.
Required Skills & Experience
- Solid grounding in Natural Language Processing and Computer Vision well-versed in mainstream models, their principles, strengths, and typical applications, with the ability to craft suitable technical solutions.
- Proficient with deep-learning frameworks such as PyTorch familiar with the architecture and implementation of models like Transformer, BERT, LLaMA, LLaVA and related extensions.
- Hands-on experience designing production architectures for large-model applications (e.g., chatbots, RAG pipelines, intelligent agents).
- Fluency in at least one programming language such as Python, C++, or Java, and comfortable working in a Linux environment.
Preferred Qualifications
- Core contributor to a high-impact open-source project.
- Publications in leading journals or conferences.
- Top rankings in well-known competitions.
- Awards in programming or mathematical-modeling contests.
