We are seeking a highly skilled AI Engineer with strong expertise in building, fine-tuning, and deploying advanced AI/ML solutions. The ideal candidate will have hands-on experience with LLMs, NLP, and RAG systems, and a proven track record of implementing scalable AI applications on cloud platforms.
*Key Skills:*
- Design, develop, and optimize AI/ML models with a primary focus on NLP and LLM applications.
- Fine-tune large language models (LLMs) and design effective prompt engineering strategies.
- Build and deploy Retrieval-Augmented Generation (RAG) systems using vector databases (e.g., Pinecone, Weaviate, FAISS, Milvus).
- Leverage frameworks such as Hugging Face Transformers, LangChain, and LlamaIndex for advanced AI solutions.
- Collaborate with cross-functional teams to integrate AI models into business applications.
- Deploy and manage AI workloads efficiently on AWS, Azure, or GCP.
- Utilize Docker and Kubernetes for containerized deployment of AI services.
- Explore and implement AI models for multilingual NLP, with an emphasis on Indic languages.
- (Preferred) Apply AI techniques in healthcare and medical domains for domain-specific solutions.
*Required Skills and Qualifications:*
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or related fields.
- 2–5 years of proven experience in AI/ML development, specifically in NLP and LLMs.
- Expertise in:
- Transformers (Hugging Face, LangChain, LlamaIndex)
- LLM fine-tuning & prompt engineering
- RAG architectures & vector databases (Pinecone, Weaviate, FAISS, Milvus)
- Proficiency in Python, with experience in PyTorch and/or TensorFlow.
- Strong background in cloud-based AI deployment (AWS, Azure, GCP).
- Experience in containerization & orchestration tools (Docker, Kubernetes).
- Familiarity with multi-language NLP, with exposure to Indic languages preferred.
- Knowledge of medical AI models will be considered an added advantage.
