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- Tasks: Join AWS Polly to innovate in speech synthesis using deep learning and generative AI.
- Company: Evi Technologies Limited is part of Amazon, leading advancements in cloud-based text-to-speech technology.
- Benefits: Enjoy a collaborative environment, access to vast resources, and opportunities for impactful research.
- Why this job: Be at the forefront of AI innovation, shaping the future of natural speech generation.
- Qualifications: PhD or Master's in relevant fields; programming skills in Java, C++, or Python required.
- Other info: Diverse and inclusive workplace focused on empowering employees and fostering creativity.
The predicted salary is between 36000 - 60000 £ per year.
Job ID: 2999882 | Evi Technologies Limited
AWS Polly is looking for a passionate, talented, and inventive Applied Scientist with a strong deep learning background to help advance the state of the art in Generative AI for speech synthesis. Polly powers natural-sounding Text-to-Speech (TTS) voices at scale and is evolving into a platform that leverages Large Language Models (LLMs) and multimodal architectures to deliver expressive, high-fidelity speech across hundreds of languages and voices.
Key job responsibilities
As an Applied Scientist on AWS Polly team, you will be part of a fast-moving and collaborative environment where scientific innovation meets customer impact. You will research and develop advanced deep learning techniques, with a focus on LLMs and transformer-based architectures, to push the boundaries of natural speech generation. Your work will span areas such as prosody modeling, speech style transfer, multilingual synthesis, and controllable voice cloning, leveraging Amazon’s vast compute infrastructure and rich multimodal datasets.
You will be responsible for designing and experimenting with novel speech generation systems that combine text, phonetics, and audio to produce lifelike, contextually appropriate speech. Your models will be trained at scale and optimized for performance, latency, and quality to meet the rigorous standards of AWS production systems.
Collaboration is core to the role: you’ll work closely with other applied scientists, engineers, and product managers to translate research into customer-facing capabilities. You’ll also partner with teams across AWS AI/ML, including those working on Bedrock, Alexa, and Amazon Connect, to ensure Polly’s speech technology integrates seamlessly into broader generative AI experiences.
As a scientific leader, you will regularly communicate your findings through technical papers, internal design documents, and presentations. Your ability to distill complex models and experiments into actionable insights will influence the direction of both product development and future research initiatives at Amazon.
About the team
AWS Polly is Amazon’s cloud-based text-to-speech service. We deliver lifelike voices and scalable APIs to customers around the world. The Polly science team builds next-generation speech generation models using LLMs and multilingual training pipelines. We are part of AWS, driving innovation in multimodal generative AI.
This role is ideal for scientists who want to work at the intersection of speech, language, and deep generative modeling, and who are excited by the challenge of bringing research to production at scale.
BASIC QUALIFICATIONS
– PhD, or a Master\’s degree and experience in CS, CE, ML or related field
– Experience in patents or publications at top-tier peer-reviewed conferences or journals
– Experience programming in Java, C++, Python or related language
– Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
– Experience in building machine learning models for business application
PREFERRED QUALIFICATIONS
– Experience using Unix/Linux
– Experience in professional software development
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page ) to know more about how we collect, use and transfer the personal data of our candidates.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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Applied Scientist, AWS Polly employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist, AWS Polly
✨Tip Number 1
Familiarise yourself with the latest advancements in deep learning, particularly in LLMs and transformer-based architectures. This knowledge will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of speech synthesis and generative AI. Attend relevant conferences or webinars where you can meet experts and learn about their work, which could give you insights that are valuable for your application.
✨Tip Number 3
Prepare to discuss your previous research and projects in detail, especially those related to speech generation or machine learning. Be ready to explain your methodologies and the impact of your work, as this will demonstrate your expertise and passion for the field.
✨Tip Number 4
Showcase your collaborative skills by highlighting any past experiences where you worked in interdisciplinary teams. Since collaboration is key in this role, demonstrating your ability to work well with others will make you a more attractive candidate.
We think you need these skills to ace Applied Scientist, AWS Polly
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your deep learning background and relevant experience in speech synthesis or generative AI. Use specific examples of projects or research that align with the responsibilities mentioned in the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for advancing speech technology and how your skills can contribute to AWS Polly's goals. Mention any relevant publications or patents to showcase your expertise in the field.
Showcase Technical Skills: Clearly outline your programming skills in languages like Python, Java, or C++. Include any experience with machine learning models and algorithms, as well as familiarity with Unix/Linux systems, as these are preferred qualifications.
Highlight Collaboration Experience: Since collaboration is key in this role, provide examples of past teamwork experiences where you worked closely with other scientists or engineers. Emphasise your ability to communicate complex ideas effectively, as this will be crucial in translating research into practical applications.
How to prepare for a job interview at Amazon
✨Showcase Your Deep Learning Expertise
Make sure to highlight your experience with deep learning techniques, especially in relation to LLMs and transformer-based architectures. Be prepared to discuss specific projects or research you've conducted that demonstrate your ability to push the boundaries of natural speech generation.
✨Prepare for Technical Questions
Expect technical questions related to algorithms, data structures, and machine learning model development. Brush up on your programming skills in languages like Python, Java, or C++, and be ready to solve problems on the spot or explain your thought process clearly.
✨Demonstrate Collaboration Skills
Since collaboration is key in this role, be ready to share examples of how you've worked effectively in teams. Discuss any experiences where you partnered with engineers or product managers to translate research into practical applications, as this will show your ability to work in a fast-moving environment.
✨Communicate Complex Ideas Clearly
You’ll need to convey complex models and experiments in an understandable way. Practice summarising your research findings and be prepared to discuss how they can influence product development. This will showcase your ability to distill information into actionable insights.
