Job Description
Are you excited about developing agentic AI, LLM and computer vision models that revolutionize Amazon's Fulfillment network? Are you looking for opportunities to apply state-of-the-art AI on real-world - PhD, or a Master's degree and experience in solving business problems through machine learning, data mining and statistical algorithms - Experience in building models for business application - Experience in patents or publications at top-tier peer-reviewed conferences or journals - Strong programming proficiency in Python with production-quality code standards; deep technical expertise with PyTorch and proficiency with the modern ML stack (Pandas, NumPy, scikit-learn, Hugging Face Transformers) - Demonstrated ability to design and execute end-to-end ML projects from research through production deployment, with experience in model monitoring and iterative improvement - Strong expertise in modern deep learning architectures including transformers and diffusion models, with hands-on experience in training optimization techniques (distributed training, mixed precision, gradient accumulation) and model compression methods (quantization, pruning, distillation) - Experience fine-tuning large language models (GPT, LLaMA, Claude) and vision-language models (CLIP, LLaVA, Qwen) - Proven experience developing agentic AI systems using state-of-the-art frameworks (LangChain, Strands, etc.) with ability to design tool-augmented reasoning systems, RAG systems, and advanced prompt engineering techniques (chain-of-thought, few-shot) - Strong knowledge and hands-on experience across multiple ML domains including computer vision (object detection, segmentation, classification), natural language processing (text generation, information extraction), and multimodal learning - Understanding of ML systems design including model serving infrastructure, A/B testing frameworks, and MLOps best practices
