Senior Applied Scientist, Translation Services

Amazon Amazon · Big Tech · IN, TS, Hyderabad · Data Science

Senior Applied Scientist role focused on applying advanced NLP and LLM techniques to improve machine translation quality and pipeline efficiency for Amazon's e-commerce platform. The role involves architecting and implementing scalable ML solutions, driving data analysis, and pioneering modeling techniques for translation quality assessment and optimization. The scientist will also serve as an expert in LLM applications for translation and mentor team members.

What you'd actually do

  1. Lead and innovate in applying advanced NLP and LLM techniques to solve complex language translation challenges in e-commerce, driving product-level improvements for our international marketplaces. Drive innovation on Image and Video translation.
  2. Architect and implement novel, scalable machine learning solutions that enhance translation quality evaluation and improve translation pipeline efficiency across multiple teams and systems.
  3. Spearhead cross-functional collaborations to define strategic project requirements, establish organization-wide success metrics, and deliver high-impact solutions aligning with broader business objectives.
  4. Drive comprehensive data analysis to uncover non-obvious insights in multilingual data, relaying findings into actionable strategies that influence product roadmaps and capabilities for language technologies.
  5. Pioneer and implement modeling techniques for machine translation quality assessment and pipeline optimization, leading the team's scientific agenda. Invent new methodologies when existing approaches fall short, advancing the state-of-the-art.

Skills

Required

  • 3+ years of building machine learning models for business application experience
  • PhD, or Master's degree and 5+ years of applied research experience
  • Experience programming in Java, C++, Python or related language
  • Experience with neural deep learning methods and machine learning

Nice to have

  • 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.

What the JD emphasized

  • minimal human touch involved in any language translation
  • accurate translated text is available
  • minimal human touch
  • accurate translated text

Other signals

  • applying advanced NLP and LLM techniques
  • enhance translation quality evaluation
  • improve translation pipeline efficiency
  • modeling techniques for machine translation quality assessment and pipeline optimization
  • Invent new methodologies
  • LLM applications for e-commerce translation