Sr. Applied Scientist, Engine AI Center of Excellence (AICE)

Amazon; Berlin; Vor Ort; EUR 65.000 - 100.000; Vollzeit

Zusammenfassung

Ein innovatives Unternehmen sucht einen erfahrenen angewandten Wissenschaftler, der komplexe maschinelle Lernprobleme löst. In dieser Rolle arbeiten Sie an der Entwicklung von Modellen zur Automatisierung kritischer Dienste und zur Verbesserung der Benutzererfahrung. Sie nutzen fortschrittliche Techniken wie neuronale Netze und probabilistische Modelle, um Lösungen für große Datenmengen zu entwickeln. Diese Position bietet die Möglichkeit, in einem dynamischen Team zu arbeiten, das sich auf die Anwendung von maschinellem Lernen in einer Vielzahl von Produkten konzentriert. Wenn Sie eine Leidenschaft für Technologie haben und Herausforderungen lieben, könnte dies Ihre nächste große Gelegenheit sein.

Qualifikationen

• Erfahrung im Aufbau von maschinellen Lernmodellen für Geschäfts Anwendungen.
• Dokumentierte Expertise in maschinellem Lernen und künstlicher Intelligenz.

Aufgaben

• Mapping von Geschäftschallenges zu Lösungen im Bereich maschinelles Lernen.
• Entwicklung und Implementierung von Modellen und Datenverarbeitungspipelines.

Kenntnisse

Maschinelles Lernen

Python

Java

C++

Datenverarbeitung

Neurale Netze

Statistische Analyse

Optimierung

Text Mining

Ausbildung

PhD in Informatik oder verwandtem Bereich

Tools

Maschinenlern-Frameworks

Verteilte Speichersysteme

Datenverarbeitungsframeworks

Datenvisualisierungstools

Jobbeschreibung

Sr. Applied Scientist, Engine AI Center of Excellence (AICE)

Stellen-ID: 2946576 | Amazon Development Center Germany GmbH

Our team builds data-driven automation capabilities to support critical service operations in Retail and IT with global impact. Automation improves the operations and availability of consumer services with a positive impact on experience of millions of users every year. Our work increases service operation resilience, automates incident response process and enables us to act ahead of service disruptions, while simplifying system and information complexity. We invent practical approaches within application areas such as anomaly detection, time series analysis, classification, causal inference, and text mining, and we apply the latest and most sound techniques of agentic workflows with Large Language Models (LLMs), probabilistic modelling, estimation and deep neural networks. Working with us offers exciting challenges where you will grow as an applied scientist and technical leader, combining your scientific and engineering skills to solve complex machine learning problems together with our tech teams around the world.

Key job responsibilities

As a Sr. Applied Scientist of the Engine AICE team, you have the important role of mapping business challenges to high-impact solutions in areas where the business problem or opportunity may not yet be defined. You turn theoretically sound methods into practically applicable models designed for processing massive volumes of data in large-scale environments. You define business relevant solutions implemented as end-to-end machine learning functions and data processing pipelines that integrate with our partners production systems. In a fast-paced innovation environment, you advise and work closely with our Applied Scientists, Machine Learning Engineers, Software Development Engineers, and partner teams to design machine learning models and experiments at scale. You are recognized for your expertise in all aspects of the practical machine learning development cycle, encompassing sound use of data pre-processing techniques, analysis, modelling, and validation methods. You take lead of the scientific and technical work in cross-team collaborations.

A day in the life

Almost everyday offers new challenges and opportunities for growth. Where one day will offer deep dives into technical requirements and applicability of state-of-the-art models to automated detection and root cause analysis of service disruptions, the next day may be focused on experimental design and implementation of model evaluations. Later in the week, you may sort technical and business requirements with our partners to help them enrich their products with our models. On some days or weeks, you may dive deep into the performance of deployed models to decide and communicate the next steps of model maintenance to our partners.

About the team

We work back to back to address the technical challenges of automation across a variety of products, software, and systems. Our scientists and machine learning engineers work in synergy to solve hard problems and enrich each other's skills. Together, we are a diverse team of specialists that bring the potential of practical machine learning to the max with impact on millions of Amazon customers.

GRUNDQUALIFIKATIONEN

1. PhD degree in Computer Science or related field
2. Several years experience building machine learning models for business applications using Python, Java, C++ or related language.
3. Documented expertise in machine learning/artificial intelligence: data processing, neural networks, deep learning, estimators, regression, information theory, optimization, statistical analysis, signal processing, graph mining, causality analysis.
4. Experience with patents or scientific publications at peer-reviewed conferences or journals and generally excellent writing and communication skills.

BEVORZUGTE QUALIFIKATIONEN

1. Experience in any of the following or similar areas: anomaly detection, time series analysis, LLM-agents, correlation analysis, causality modelling, graph modelling, probabilistic modelling, nlp, text mining.
2. Experience in data-driven and automated fault/incident management and service reliability systems at scale.
3. Experience with machine learning frameworks, distributed storage systems, or data processing frameworks, and data visualization tools.
4. Experience in designing and developing large, scalable production systems and architectures.
5. Project leader and/or team lead experience.

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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