Applied Scientist Torino

Applied Scientist
Torino
Piemonte, Torino

DESCRIPTION

The Devices team seeks an Applied Scientist with a strong background in machine and deep learning to spearhead the advancement and deployment of state of the art ML/RAG systems.

As part of this team, you will collaborate with talented peers to create scalable solutions for an innovative conversational assistant, aiming to revolutionize user experiences for millions of Alexa customers.

Creating reliable, scalable and high performance products requires exceptional technical expertise, and a sound understanding of the fundamentals of Machine Learning, NLP, LLM, and Problem solving.

This role requires working closely with business, engineering and other scientists within the team and across Amazon to raise the bar in operational excellence, improving tools and automating workflows.

You will lead high visibility and high impact programs collaborating with various teams across Amazon.

The candidate is self-motivated, thrives in ambiguous and fast-paced environments, possesses the drive to tackle complex challenges, and excels at swiftly delivering impactful solutions while iterating based on user feedback.

Join us in our mission to redefine industry standards and provide unparalleled experiences for our customers.

Key job responsibilities Analyze, understand, and model customer behavior and the customer experience based on large scale dataBuild and measure novel online & offline metrics for personal digital assistants and customer scenarios, on diverse devices and endpointsCreate, innovate and deliver deep learning, policy-based learning, and/or machine learning based algorithms to deliver customer-impacting resultsBuild and deploy automated model training and evaluation pipelinesPerform model/data analysis and monitor metrics through online A/B testingResearch and implement novel machine learning and deep learning algorithms and modelsResponsible for on-call duties during peak and non-peak hours, deploying fixes, and handling high-sev issues working with Software Developer Engineers BASIC QUALIFICATIONS PhD, or a Master's degree and experience in Computer Science, Computer Engineering, Machine Learning or related fieldExperience building machine learning models or developing algorithms for business applicationBar raising knowledge of programming languages such as Python or Java, with a strong focus on machine learning frameworksExperience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingUnderstanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. Excellent communication skills (written & spoken) and ability to collaborate effectively in a distributed, cross-functional team settingFluency in written and spoken English PREFERRED QUALIFICATIONS 5+ years of building machine learning models or developing algorithms for business application experienceHave publications at top-tier peer-reviewed conferences or journalsTrack record of diving into data to discover hidden patterns and conducting error/deviation analysisAbility to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relationsExceptional level of organization and strong attention to detailComfortable working in a fast paced, highly collaborative, dynamic work environment

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.

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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.

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