: Principal Applied Scientist
101 Main Street
Cambridge, MA 02142

Employee Testimonials



The principal scientist will initiate and work on key initiatives for developing and advancing world-leading wakeword and embedded ML technology for any voice-driven Alexa end-point. The goal is to achieve unmatched wakeword recognition accuracy for any device - low CPU/memory footprint - in any acoustic environment, for any speaker, and under challenging noise conditions such as barge-in. You will be responsible for analyzing system short-comings, for leading the development of data-driven and algorithmic improvements, for defining the path to production, and for influencing design and architecture of goal-relevant software. You will work in a hybrid, fast-paced organization where scientists and engineers work jointly together and drive improvements directly to production.
The principal scientist will either go deep on a specific area like multi-channel and noise robust acoustic modeling for a conversational agent and act as a technical lead, or will work across teams and areas influencing data, algorithm, and design decisions. Areas of interest cover the whole acoustic modeling and embedded ML spectrum, including multi-channel raw audio input acoustic modeling, noise robust acoustic modeling, device and speaker independent acoustic modeling, acoustic model adaptation, advanced deep learning for acoustic and language modeling, active learning and semi-/unsupervised learning techniques for acoustic and language modeling, learning from heterogeneous and mismatched audio data including data selection and data simulation, multi-lingual speech, quantization aware training, Federated ML, speaker adaptation, etc.

The principal scientist will help driving scalable, robust, and automated solutions, making new algorithms and processes scalable to work on production-scale data sizes and achieving fully automated adaptation of processes and algorithms to new environments and to other locales. You will also help integrating new algorithms and processes into existing modeling stacks, simplify and streamline the existing modeling stacks, and develop testing and evaluation strategies. You will influence design and architecture of software stacks used offline and at runtime for building and deploying model artifacts, achieving flexible yet efficient solutions suitable for R&D work and for running in production. You will mentor and coach junior scientists to raise the bar of scientific research within Amazon.


· Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, or Mathematics with at least 7 years of related work experience
· Domain expertise in acoustic modeling for speech recognition and/or embedded machine learning, familiarity with deep learning for speech recognition
· Familiarity with machine learning and statistical modeling techniques, scientific thinking, and the ability to invent
· Familiarity with programming languages such as C/C++ and Python


· PhD with specialization in speech recognition and machine learning
· Strong publication record
· Strong software design and development skills
· Experience working effectively with science, data processing, and software engineering teams
· Proven track record of innovation and advancing the state of the art
· Entrepreneurial spirit combined with strong architectural and problem solving skills
· Excellent written and spoken communication skills


Employee Testimonials

Spyros M.
Senior Principal Scientist, Alexa Machine Learning

“For scientists, this is a great place for doing research because Amazon is very data-driven and metrics-oriented. The rigor expected in scientific publications in terms of running controlled experiments and tracking progress based on well-established metrics is exactly what we see in our team.”

“You also interact with people with strong technical and practical experience and learn from each other,” he says. “You’re exposed to a breadth of challenges, many of them long-term applications for artificial intelligence."

Chao W.
Alexa Science Manager

“Since 2000 I’ve been focused on developing spoken language and machine translation systems that can engage with humans more effectively, and hopefully break down language and other barriers,” Chao says. “We’re still far from systems that truly understand the meaning of what we’re saying, but the progress we’re making with Alexa is incredibly exciting.”

Janet S.
Senior Manager of Applied Modeling and Data Science

“We have much further to go in developing systems that can truly understand and converse with humans naturally.  But I’m incredibly proud of how far we’ve come with Alexa, and super excited about the work teams are doing to make Alexa smarter every day.”

Shankar A.
Senior Manager, Applied Science

“When I first joined the team I didn’t realize just how big and ambitious this initiative really is,” said Shankar. “What’s incredibly exciting for speech scientists like myself is how algorithmic innovations in machine learning and data science have created a sophisticated voiced-based AI like Alexa, and how our work on improving this technology has a positive impact on the day-to-day lives of millions of customers using it."

Chris C.
People Manager

“We have an incredibly diverse, experienced and curious team that is always pushing the envelope even further! Here at Amazon, we pride ourselves on being peculiar. We bring in talent from all around the world, leading to a diversity of background, culture and perspective in each team!” 

Beatriz R.
Team Manager

“I have quickly learned that Amazon is a company where you can actually voice out your ideas and concerns, where you can expect the support and interest of Leadership. We are quick to take action, passionate about improving processes and driven to enhance morale, so being able to speak up without fear has been my best asset. Now at the year mark at ADS, I am happy to say that the culture is one where you are proud to be a member of the team. “