Applied Scientist, Artificial General Intelligence, AGI Information

Amazon; Berlin; Vor Ort; EUR 70.000 - 100.000; Vollzeit

Zusammenfassung

A multinational technology company in Berlin is seeking an Applied Scientist to develop cutting-edge Generative AI technology with Large Language Models (LLMs). The successful candidate will innovate within a fast-paced environment, work collaboratively with various teams, and be responsible for designing experiments and building solutions to meet customer needs. Strong background in machine learning and LLM post-training techniques required. Competitive compensation and an inclusive company culture offered.

Qualifikationen

• PhD, or a Master's degree and experience in CS, CE, ML or related field.
• Experience in designing experiments and statistical analysis.
• Familiarity with post-training techniques for LLMs.

Aufgaben

• Design and execute experiments to evaluate performance of algorithms.
• Build solutions addressing customer needs with informed trade-offs.
• Develop novel algorithms or techniques to advance LLMs.

Kenntnisse

Large Language Models

Natural Language Processing

Machine Learning

Statistical Analysis

Programming in Java, C++, Python

Ausbildung

PhD or Master's degree in CS, CE, ML or related field

Tools

MxNet

TensorFlow

Unix/Linux

Jobbeschreibung

Description

We are looking for a passionate, talented and inventive Applied Scientist to develop industry-leading Generative Artificial Intelligence (GenAI) technology with Large Language Models (LLMs). In this role, you will innovate in the fastest-moving fields of current AI research, in particular developing state-of-the-art foundation models capable of processing a broad range of prompts and information in many languages.

If you are deeply familiar with Large Language Model development, natural language processing and machine learning, this may be the right opportunity for you. Our fast-paced environment requires a high degree of independence in making decisions and driving ambitious research agendas all the way to production. You will work with other science and engineering teams across AGI, as well as business stakeholders to maximize velocity and impact of your team's contributions.

Key job responsibilities

• Design and execute experiments to evaluate the performance of post-training algorithms and data, and iterate quickly to improve results.

• Build solutions that address customer needs, making informed trade-offs to balance accuracy, efficiency, and user experience.

• Work with peers to develop novel algorithms or modeling techniques to advance the state of the art with LLMs.

About the team

The AGI team has a mission to push the envelope in LLMs and multimodal systems, in order to provide the best-possible experience for our customers.

Basic Qualifications

• PhD, or a Master's degree and experience in CS, CE, ML or related field

• Experience in designing experiments and statistical analysis of results

• Experience programming in Java, C++, Python or related language

• Experience with deep learning and/or machine learning, post-training techniques for LLMs (SFT, DPO, PPO etc.), natural language processing.

Preferred Qualifications

• Experience using Unix/Linux

• Experience in patents or publications at top-tier peer-reviewed conferences or journals

• Experience with popular deep learning frameworks such as MxNet and Tensor Flow

• Experience in professional software development

• Experience building machine learning models or developing algorithms for business application

• Hands-on experience in training and evaluating LLMs

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

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