Come join the Alexa AI Deep Learning Science team, building the speech and language AI solutions behind Amazon Echo and other Amazon products and services! You will help us invent the future.
Alexa has some of the world’s most challenging AI problems to solve. To keep our customers delighted and engaged, we need to not only keep pace with the advances in AI, but we also need to push the envelope and keep producing world class AI research. Challenges related to building these AI models include (1) training with massive amounts of data, (2) training with fewer labeled data points, (3) deploying more and more of these models in resource constrained edge devices and (4) keeping our customers data private and safe. The Deep Learning Science team in Alexa AI invests in privacy-preserving distributed deep learning at scale, AutoML building blocks, inference optimization as well as active and weakly-supervised learning research to enable teams across Alexa address these challenges.
As a Senior Applied Scientist in the team, you will research and create models, improve models for natural language processing and speech recognition problems. You will gain hands-on experience with Amazon’s heterogeneous structured data sources; as well as large-scale computing resources to accelerate advances in training deep neural networks for natural language understanding and automatic speech recognition on massive amounts if text and speech data. The ideal candidate is clearly passionate about delivering experiences that delight customers and creating solutions that are robust.
As a Senior Applied Scientist in the team, you’ll mentor and develop other scientitsts in the team, drive cross team collaborations with partner science teams in NLU, ASR and Conversational AI organizations. You’ll also help the team and the management define the roadmap for the the science team and the sister platform team. You’ll drive science best practices across multiple team and within the organization.
Creating reliable, scalable and high performance products requires exceptional technical expertise, and a sound understanding of the fundamentals of Machine Learning. We value academic collaborations and encourage our scientists and engineers to publish in top conferences such as NIPS, ICML, ICLR, KDD etc. and do open source contributions.
· PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
· 3+ years of experience of building machine learning models for business application
· Experience programming in Java, C++, Python or related language
· Master's degree in Machine Learning, Computer Science, Electrical Engineering, Mathematics or related field, or related industry experience
· 5+ years of experience with underlying Machine Learning techniques, Deep Learning, and algorithm development
· 5+ years of software development experience
· 5+ years of experience in state-of-the-art machine learning and statistical modeling techniques
· Development experience in programming languages C/C++, Python and/or Java
· PhD degree in machine learning, computer science or related discipline
· 5+ years of industry or postdoctoral experience with machine learning
· 5+ years of experience in natural language understanding/processing or speech recognition
· 5+ years of tech lead experience
· Experience in building large-scale machine learning systems
· Strong object-oriented design and coding skills (C/C++ and/or Python on Linux platform)
· Proficiency in cuda
· Proficiency in MxNet, pyTorch or TensorFlow
· Excellent communication, design and analytical skills
· Publications at top-tier peer-reviewed conferences or journals
Amazon is an Equal Opportunity-Affirmative Action Employer – Minority / Female / Disability / Veteran / Gender Identity / Sexual Orientation
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