Applied Scientist - generative AI, AGI

Evi Technologies Limited
Cambridge
2 months ago
Applications closed

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Applied Machine Learning Researcher

Data Scientist | London | AI-Powered SaaS Company

Our team builds generative AI solutions that will produce some of the future’s most influential voices in media and art. We develop cutting-edge technologies with Amazon Studios, the provider of original content for Prime Video, with Amazon Game Studios and Alexa, the ground-breaking service that powers the audio for Echo.

Do you want to be part of the team developing the future technology that impacts the customer experience of ground-breaking products? Then come join us and make history.

We are looking for a passionate, talented, and inventive Applied Scientist with a background in Machine Learning to help build industry-leading Speech, Language, Audio and Video technology.

As an Applied Scientist at Amazon you will work with talented peers to develop novel algorithms and generative AI models to drive the state of the art in audio (and vocal arts) generation.

Position Responsibilities:

* Participate in the design, development, evaluation, deployment and updating of data-driven models for digital vocal arts applications.
* Participate in research activities including the application and evaluation and digital vocal and video arts techniques for novel applications.
* Research and implement novel ML and statistical approaches to add value to the business.
* Mentor junior engineers and scientists.

BASIC QUALIFICATIONS

- Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Experience with programming languages such as Python, Java, C++

PREFERRED QUALIFICATIONS

- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals

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