Senior Python Developer (Generative AI & LLMs)

Job Description

Role & responsibilities Develop and optimize Generative AI models and LLM-based applications . Design and implement high-performance, scalable RESTful APIs . Work with AI/ML frameworks such as TensorFlow, PyTorch, or JAX to build scalable AI solutions . Design and manage datasets for training and fine-tuning LLMs. Implement memory-efficient techniques for optimizing large-scale AI models. Develop and refine prompt engineering strategies to enhance model performance. Integrate and optimize LLM-based APIs and libraries for real-world applications. Work with transformer-based models to build conversational and contextual AI solutions. Optimize backend performance using caching, asynchronous processing, and distributed systems . Develop data pipelines to support AI/ML workflows, including preprocessing, model inference, and retrieval-augmented generation (RAG) . Work with vector databases (Pinecone, Weaviate, FAISS) for semantic search and efficient information retrieval. Ensure production readiness with robust logging, monitoring, and cloud-based deployment ( AWS, GCP, Azure ). Stay updated with the latest advancements in LLMs, NLP, and AI technologies . Preferred candidate profile 6+ years of experience in Python development with a focus on core product development. Strong expertise in Generative AI, LLMs, and AI/ML frameworks (PyTorch, TensorFlow, JAX). Experience integrating LLMs via APIs, SDKs, or fine-tuning models . Hands-on experience with prompt engineering techniques for AI model optimization. Proficiency in Hugging Face Transformers, LangChain, OpenAI API , and similar libraries. Experience with data preprocessing, augmentation, and training pipelines . Strong knowledge of vector databases, embeddings, and retrieval-augmented generation (RAG) . Hands-on experience with relational databases (PostgreSQL, MySQL) and performance-optimized SQL queries . Familiarity with transformer models, tokenization techniques, and deep learning architectures . Experience in cloud-based infrastructure (AWS, GCP, Azure) and infrastructure automation. Strong debugging, optimization, and performance tuning skills for high-scale backend applications. Perks and benefits