Generative AI Engineer

About the job

Overall 5+ years of experience in IT Industry Good Exposure in Python, Gen AI. Key Responsibilities • Develop, train, fine-tune, and deploy generative AI models (LLMs, diffusion, transformers, etc.) for various use cases (text, image, or multimodal). • Design and maintain scalable ML pipelines using Python, PyTorch, TensorFlow, or JAX. • Integrate LLM APIs (OpenAI, Anthropic, Hugging Face, etc.) and build domain-specific wrappers or agents. • Optimize model inference, prompt engineering, and response quality for production use. • Collaborate with data engineers and product teams to define data requirements, evaluate models, and deliver end-to-end AI features. • Implement best practices in model evaluation, versioning, monitoring, and responsible AI usage. • Stay current with advancements in generative AI, reinforcement learning, and multimodal architectures. Required Skills • Strong command of Python (async programming, packaging, APIs, data structures). • Solid experience with one or more deep learning frameworks: PyTorch, TensorFlow, JAX. • Experience working with LLMs (e.g., GPT, Claude, LLaMA, Mistral) and/or diffusion models (e.g., Stable Diffusion, Midjourney API, etc.). • Understanding of transformer architectures, tokenization, and embedding techniques. • Experience with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma) and retrieval-augmented generation (RAG). • Proficiency in API design, data pipelines, and cloud ML deployment (AWS, GCP, or Azure). • Familiarity with prompt engineering, few-shot learning, and model evaluation techniques.