Applied Scientist

Audible; Berlin; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

Audible GmbH is seeking an Applied Scientist to build scalable ML/NLP models and GenAI features that power product experiences for millions of listeners. You will collaborate with scientists, engineers, and product teams to design and deploy production-ready solutions at scale.

The role emphasizes building robust components, evaluating models with data-driven judgment, and contributing to cutting-edge AI research while delivering impactful customer outcomes.

Qualifikationen

• Advanced degree in a quantitative field with strong ML/NLP background.
• 1st item
• Proven experience in deploying production ML/AI solutions.

Aufgaben

• Design, develop and deploy models for Content Understanding and GenAI features.
• 2nd item
• Collaborate with scientists and engineers to productionize models.
• 3rd item
• Contribute to research and publish when applicable.
• 4th item
• Evaluate models and mitigate risk while improving customer experience.

Kenntnisse

Data structures

Algorithm design

Statistics

System design

Deep Learning

NLP

GenAI

Reinforcement Learning

Python

SQL

Java

C++

LLMs

AWS SageMaker

Ausbildung

MSc + 5y relevant exp

PhD + 1y relevant exp

Tools

Python

SQL

Java

C++

AWS

SageMaker

Jobbeschreibung

Description

At Audible, we believe stories have the power to transform lives. It’s why we work with some of the world’s leading creators to produce and share audio storytelling with our millions of global listeners. We are dreamers and inventors who come from a wide range of backgrounds and experiences to empower and inspire each other. Imagine your future with us.

About This Role

As an Applied Scientist, you will solve large complex real-world problems at scale, draw inspiration from the latest science and technology to empower undefined/untapped business use cases, delve into customer requirements, collaborate with tech and product teams on design, and create production-ready models that span various domains, including Machine Learning (ML), Artificial Intelligence (AI) and Generative AI, Natural Language Processing (NLP), Reinforcement Learning (RL), real-time and distributed systems.

About You

Your work will focus on inventing or adapting scientific approaches, models, and algorithms driven by customer needs at the project level. You will develop components and/or end-to-end solutions that are deployed into production or directly support production systems, delivering consistently high-quality work that meets both scientific and engineering best practices. You will develop reusable science components and services that resolve architecture deficiencies and customers’ pain points, while making technical trade-offs for long-term/short-term. You will work semi-autonomously to deliver solutions, contribute to research papers at peer-reviewed venues when appropriate, and document your work thoroughly to enable others to understand and reproduce it. Your decision-making will consistently incorporate robust, data-driven business and technical judgment. You will collaborate with other scientists to raise the bar of both scientific and engineering complexity for the team and to foster valuable scientific partnership opportunities to help/guide science decisions. We work in a highly collaborative, fast-paced environment where scientists, engineers, and product managers work to test and build scalable foundational capabilities, as well as customer facing experiences. You will have the opportunity to innovate and think big within your projects scope, implement optimization services and algorithms, and influence the experiences of millions of customers.

We are looking for a results-oriented Applied Scientist with deep knowledge in ML, NLP, Deep Learning, GenAI, and/or large-scale distributed computation.

As an Applied Scientist, you will…

• Understand use cases across the business and adopt/extend/design/invent solutions/models that are scalable, efficient, and automated for difficult problems that are not well defined
• Work closely with fellow scientists and software engineers (at Audible and Amazon) to build and productionize models, deliver novel and highly impactful features
• Review models of peers for the purpose of reducing and managing risk to the business, while improving customer experience
• Design, develop, and deploy modeling techniques and solutions for Content Understanding, Recommendations, GenAI-based product features, by employing a wide range of methodologies, working from simple to complex
• Contribute to initiatives that employ the most recent advances in ML/AI in a fast-paced, experimental environment
• Push the boundary of innovation

About Audible

Audible is the leading producer and provider of audio storytelling. We spark listeners’ imaginations, offering immersive, cinematic experiences full of inspiration and insight to enrich our customers daily lives. We are a global company with an entrepreneurial spirit. We are dreamers and inventors who are passionate about the positive impact Audible can make for our customers and our neighbors. This spirit courses throughout Audible, supporting a culture of creativity and inclusion built on our People Principles and our mission to build more equitable communities in the cities we call home.

Basic Qualifications

• Knowledge of data structures, algorithm design, statistics, and system design
• MSc + 5ys of relevant experience, or PhD +1 year in one of the following disciplines: Machine Learning, Computer Science, Computer Engineering, Data Science, Applied Math, or a related quantitative field
• 3+ years of experience in Deep Learning, Natural Language
• Processing/Understanding, GenAI and/or Reinforcement Learning
• Proficiency in Python, SQL, and other scripting languages
• Experience employing and innovating with LLMs/GenAI to solve complex problems

Preferred Qualifications

• 2+ years of practical machine learning experience
• Experience in agile software development methodology
• Experience with programming languages such as Python, Java, C++
• Have publications at top-tier peer-reviewed conferences or journals
• Experience with building Recommendation Systems
• Machine Learning Pipeline orchestration with AWS (SageMaker, Batch, Lambda, Step Functions) or similar cloud platforms

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.

m/w/d

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.

Company

Audible GmbH - B38

Job ID: A10373370