Senior Applied Scientist, APEX

About The Team

Alexa AI is building the science and technology behind Alexa+, Amazon's next-generation conversational assistant. Our team works at the intersection of large language models, reinforcement learning from human feedback and verifiable rewards, agentic architectures, and multilingual/multimodal understanding. We operate at massive scale — our models serve customers across dozens of languages and device types. If you want to push the frontier of conversational AI and see your work used by people every day, come join us.

Responsibilities

• Design, implement, and evaluate novel approaches to LLM fine-tuning, alignment (RLHF, DPO), and distillation for production deployment
• Develop and improve agentic systems — including multi-step reasoning, tool use, planning, and orchestration — that work reliably at scale
• Build evaluation frameworks and methodologies that go beyond standard benchmarks to capture real-world conversational quality
• Translate research advances into customer-facing products, working closely with engineering, product, and cross-functional science teams
• Analyze large-scale experimental results, identify patterns, and iterate rapidly on model improvements
• Publish results at top-tier venues and contribute to Amazon's presence in the broader research community
• Mentor junior scientists and contribute to hiring efforts

Qualifications

Basic Qualifications

• PhD/MS in Computer Science, Electrical Engineering, Machine Learning, Natural Language Processing, or a related technical field, OR Master's degree with 5+ years of relevant industry experience
• 3+ years of hands-on experience in applied machine learning, predictive modeling, or NLP
• Strong programming skills in Python or a related language
• Experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
• Track record of delivering ML/NLP solutions from research to production
• Experience working with large language models (training, fine-tuning, or evaluation)

Preferred Qualifications

• 5+ years of relevant industry or academic research experience
• Experience with LLM alignment techniques (RLHF, DPO, constitutional AI)
• Experience with agentic AI systems, including planning, tool use, and orchestration
• Experience with distributed training and large-scale model optimization
• Peer-reviewed publications at top-tier venues (e.g., NeurIPS, ICML, ACL, EMNLP, ICLR)
• Strong communication skills with the ability to present complex technical concepts to diverse audiences
• Experience mentoring junior scientists or engineers