Senior Machine Learning Scientist, Alexa AI Knowledge - London
Amazon
London, GBR
19h ago

Job summary

Come join Alexa Artificial Intelligence the science team behind Amazon’s intelligent voice assistant. Alexa AI in London is hiring an Applied Scientist who is passionate about applying advanced ML and statistical techniques to solve real-world challenges.

This role is part of the Alexa AI Knowledge team, where we research novel machine learning, computer vision and natural language processing algorithms to deliver customer-facing knowledge services such as multi-modal question answering at scale.

The team runs production services that impact millions of users globally, and researches new methods in question understanding, knowledge extraction, and information enrichment to deliver ground-breaking advances in accuracy and scale.

You will work in an agile team of scientists and engineers. As a scientist on the team, you will be involved in every aspect of the development lifecycle, from idea generation and scientific research to development and deployment of advanced models.

Our ideal candidate is an experienced ML technology scientist who has a track-record of taking invention to production. You should have a commitment to working with a diverse team as well as great leadership and communication skills.

You are passionate about using scientific research to deliver value to customers and are motivated to deliver results in a fast-paced environment.

This position offers an exceptional opportunity to grow your technical and non-technical skills and make a real difference to Alexa customers.

Key job responsibilities

  • Drive the design, development, evaluation, and deployment of data-driven solutions with machine learning (ML), natural language processing and / or computer vision approaches
  • Mentor junior scientists
  • Implement and improve modeling tools, training recipes, and prototypes utilizing programming skills in Python, Java or C++.
  • Collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems
  • Work backwards from customer needs and use that information to make trade-offs between different modeling approaches
  • Report results to technical and business audiences in a manner that is statistically rigorous and compellingly relevant, exemplifying good scientific practice in a business environment
  • Research the latest modeling techniques and stay current with advancements in the field
  • Promote the culture of experimentation and applied science at Amazon
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