Senior Applied Scientist

4 weeks ago


Floral Park NY USA, United States Amazon Full time
About This Role

We're seeking a highly skilled Applied Scientist to join our Playback team at Audible. As a key member of our team, you'll be responsible for designing and developing scalable, efficient, and automated solutions for our playback services.

You'll work closely with our team of scientists and software engineers to drive real-time model implementations and deliver novel and highly impactful features. Your expertise in machine learning, natural language processing, and deep learning will be instrumental in advancing the state-of-the-art in audio playback.

In this role, you'll have the opportunity to explore, innovate, and invent novel algorithms and services that leverage custom and industry-proven machine learning, natural language processing, and artificial intelligence technologies.

You'll be responsible for designing, developing, and deploying state-of-the-art optimization services and algorithms, as well as novel adaptive bitrate algorithms. You'll also partner closely with other Amazon scientists focused on streaming insights and optimization use cases.

As a Senior Applied Scientist, you'll be trusted to operate with independence and will be assigned to focus on areas with significant impact on audience satisfaction.

We're looking for someone who is passionate about innovation, has a strong track record of advancing the state-of-the-art in machine learning, and is committed to delivering high-quality results.

About You

We're looking for someone with a PhD in Computer Science, Machine Learning, Statistics, Data Science, Applied Math, or Operational Research. You should have a strong background in machine learning, natural language processing, and deep learning, and be proficient in Python, SQL, and Java.

You should have experience in algorithm development, machine learning pipeline orchestration with AWS, and big data engineering with Spark and AWS EMR. Domain knowledge of comparable products and publications at top-tier peer-reviewed conferences or journals is a plus.

We're committed to a diverse and inclusive workplace and are an equal opportunity employer. If you're passionate about innovation and have a strong track record of advancing the state-of-the-art in machine learning, we encourage you to apply.



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