Requirements

9+ years AI/ML experience, Python proficiency, Generative AI expertise, LLM fine-tuning, PyTorch or TensorFlow, Vector databases, RAG architectures

Skills

PythonLLMPyTorch

Design and implement scalable AI/ML models, focusing on LLMs and Generative AI use cases
Fine-tune and deploy foundation models such as GPT, LLaMA, and Mistral using Python
Lead research, experimentation, and prototyping of new ML algorithms and NLP approaches
Collaborate with data scientists, MLOps engineers, and product teams to integrate AI capabilities
Develop APIs and end-to-end ML pipelines for training, testing, and deployment
Stay current with emerging trends in artificial intelligence and apply best practices

9+ years of experience in Artificial Intelligence, Machine Learning, and Python programming
Hands-on expertise in Generative AI and Large Language Models (LLMs)
Strong knowledge of PyTorch, TensorFlow, and Hugging Face Transformers
Experience with prompt engineering, fine-tuning, and inference optimization of LLMs
Solid understanding of NLP, deep learning architectures, and model performance evaluation
Experience with vector databases (FAISS, Pinecone) and retrieval-augmented generation (RAG) architectures
Proven ability to translate complex research into scalable applications

Exposure to LangChain, OpenAI APIs, or Anthropic Claude
Familiarity with cloud platforms (AWS/GCP/Azure) and MLOps practices (Docker, MLFlow, CI/CD)
Experience mentoring junior engineers or leading AI project teams
Contributions to open-source AI projects or published research