Applied Scientist, Artificial General Intelligence - Data Services

Experteer Overview Join Amazon as an Applied Scientist to push the boundaries of NLP and ML at scale. You will build and evaluate models, ensure high data quality across acquisition and processing, and work with cross-functional teams to improve customer experiences. You’ll handle data preparation, ground truth generation, and cross-lingual tasks to enable robust AI systems. This role offers impact across products, shaping the future of human-technology interaction. Compensation / Benefits * Ensure data quality across all stages of acquisition and processing (sourcing, ground truth generation, normalization, transformation, cross-lingual mapping) * Clean, analyze and select relevant speech/language data to meet goals * Build and test models that improve customer experience * Collaborate with science, engineering, and business colleagues * Present data-backed proposals and actionable conclusions * Develop efficient data querying infrastructure for offline and online use cases Tasks * 3+ years building models for business applications * PhD, or Master’s degree and 4+ years in CS, CE, ML or related field * Experience programming in Java, C++, Python or related language * Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing * Experience using Unix/Linux Key requirements * health insurance (medical, dental, vision) * 401(k) matching * RSUs * sign-on payments * paid time off * parental leave

3+ years building models for business applications * PhD, or Master’s degree and 4+ years in CS, CE, ML or related field * Experience programming in Java, C++, Python or related language * Experience in algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing * Experience using Unix/Linux Key requirements * health insurance (medical, dental, vision) * 401(k) matching * RSUs * sign-on payments * paid time off * parental leave