Sr. Applied Scientist, C360

Description

Are you a scientist passionate about advancing Information Retrieval, NLP, and Large Language Models? Do you want access to massive datasets, world-class compute, and a team of top scientists and engineers building the future of e-commerce? If so, you'll be a great fit for our team at Amazon.

We build large-scale ML solutions that deliver personalized, up-to-date recommendations to millions of customers. Our team is uniquely positioned to shape how customers think about their shopping journey.

Key job responsibilities

• Own the scientific roadmap for personalization initiatives, identifying high-impact research directions and translating ambiguous business problems into well-defined ML formulations
• Design and lead end-to-end systems spanning recommendations, information retrieval, and LLM fine-tuning, from problem framing through offline experimentation to production A/B testing and launch
• Drive technical decisions on model architecture, training methodology, and evaluation frameworks, balancing scientific rigor with business impact and operational constraints
• Mentor and raise the bar for the science team through design reviews, paper discussions, and establishing best practices for experimentation and reproducibility
• Influence cross-functional strategy by partnering with engineering, product, and leadership to define the product vision informed by what's technically feasible and scientifically novel
• Publish and advance the state of the art — contribute to the broader ML community through patents, publications, and external engagement at conferences

About the team

The team values innovations and offers a safe place to try, fail and learn while fostering a culture of continuous improvement. Everyone is a leader and owner for everything we do as a team. Our team offers creative space with entrepreneurial work environment focusing on customer obsession.

Basic Qualifications

• 3+ years of building machine learning models for business application experience
• PhD, or Master's degree and 6+ years of applied research experience
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
• Experience with large scale distributed systems such as Hadoop, Spark etc.