Applied Scientist - Global Returns & Recommerce ML

Amazon; Factoria (WA); On-site; USD 143,000 - 193,000; Full time

Benefits offered by this job

Medical, Dental, Vision Coverage

Paid Time Off (PTO)

401(k) Plan

Parental Leave Options

Job summary

Amazon is seeking a technical leader to design, develop, and evaluate state-of-the-art NLU/LLM models within the World Wide Returns & ReCommerce team in Bellevue, WA. The role focuses on building scalable ML solutions and collaborating with data and software engineering to deploy models at very large scale.

The candidate will work with SQL, Python, Jupyter, and PyTorch to train and deploy models while mentoring interns and driving innovative approaches across the ML lifecycle.

Qualifications

• 3+ years of building models for business applications.
• PhD or Master’s degree plus 4+ years in CS/CE/ML.
• Experience programming in Java, C++, Python or related language.
• Experience building machine learning models or developing algorithms for business applications.

Responsibilities

• Design, develop, and evaluate highly innovative models for our Natural Language Understanding (NLU) and Large Language Model (LLM) models.
• Use SQL to query and analyze the data.
• Use Python, Jupyter notebook, and Pytorch to train/test/deploy NLU/LLM/GenAI models.
• Use machine learning and analytical techniques to create scalable solutions for business problems.
• Research and implement novel machine learning and statistical approaches.
• Mentor interns.
• Work closely with data & software engineering teams to build model implementations and integrate successful models and algorithms in production systems at very large scale.

Skills

3+ years of modeling

ML model development

Java/C++/Python experience

CS/CE/ML advanced degree

Education

PhD or Master’s in CS/CE/ML

Tools

Unix/Linux

Job description

Amazon is seeking a technical leader to design, develop, and evaluate state-of-the-art NLU/LLM models within the World Wide Returns & ReCommerce team in Bellevue, WA. The role focuses on building scalable ML solutions and collaborating with data and software engineering to deploy models at very large scale.

The candidate will work with SQL, Python, Jupyter, and PyTorch to train and deploy models while mentoring interns and driving innovative approaches across the ML lifecycle.