Applied Scientist III

Position Responsibilities Participate in the design, development, evaluation, deployment, and updating of data‑driven models and analytical solutions for machine learning (ML) and/or natural language (NL) applications. Apply statistical modeling techniques—including Bayesian models, deep neural networks, optimization methods, and other ML techniques—to diverse business and engineering applications. Build and deploy ML models on available data, run and analyze experiments in production, identify new research opportunities to meet business goals, and research and implement novel ML and statistical approaches to add value. Mentor junior engineers and scientists. Position Requirements • Master’s degree (or foreign equivalent) in Computer Science, Machine Learning, Engineering, or a related field with two years of research or work experience in a related occupation, or • Bachelor’s degree (or foreign equivalent) in the same fields with five years of progressive post‑baccalaureate research or work experience, considered equivalent to a Master’s degree and two years of research or work experience. One year of experience in programming with Java, C++, Python, or equivalent language. One year of experience developing supervised and unsupervised machine learning models for moderately complex projects in business, science, or engineering. Benefits and Compensation 40 hours per week; 8:00 am‑5:00 pm Salary range: $167,100/year to $226,100/year Equity, sign‑on payments, and other compensation may be provided as part of a total compensation package. Full range of medical, financial, and other benefits. Equal Opportunity Statement Amazon.com is an Equal Opportunity‑Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Job Details Location: Boston, Massachusetts Position: Applied Scientist III Department: Corporate Operations #J-18808-Ljbffr