Applied Scientist, Learned Systems Group

TN Germany; München; Vor Ort; EUR 60.000 - 100.000; Vollzeit

Zusammenfassung

An innovative firm is seeking a talented Applied Scientist to join their Learned Systems Group in Munich. This role offers the opportunity to work on cutting-edge machine learning projects, including database system challenges and algorithm development. You will collaborate with customers and academic communities while designing end-to-end solutions using C++ and Python. Join a team that values diverse experiences and fosters a culture of inclusion, mentorship, and work-life balance. If you are passionate about machine learning and eager to tackle novel problems, this is the perfect opportunity for you.

Qualifikationen

• PhD candidate or graduate in engineering, computer science, or related fields.
• Experience with patents or publications at top-tier conferences.

Aufgaben

• Design and develop end-to-end AWS database experiences using C++ and Python.
• Write technical white papers and create roadmaps for production projects.

Kenntnisse

Machine Learning

Deep Learning

C++

Python

Algorithms

Data Structures

Optimization

Robotics

Statistics

Ausbildung

PhD in Engineering

PhD in Computer Science

PhD in Machine Learning

Tools

Unix/Linux

Jobbeschreibung

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Applied Scientist, Learned Systems Group, Munich

Client: Amazon Web Services Development Center Germany GmbH

Location:

Job Category: Other

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EU work permit required: Yes

Job Reference:

2d34d7b4cd9b

Job Views:

2

Posted:

27.04.2025

Expiry Date:

11.06.2025

Job Description:

Are you a PhD candidate or graduate interested in a full-time role in 2025 in the field of Applied Sciences? Are you interested in machine learning, deep learning, automated reasoning, speech, robotics, computer vision, optimization, or quantum computing? If so, we want to hear from you! We are looking for scientists with expertise in these areas to invent, design, and implement cutting-edge solutions for novel problems.

AWS is seeking world-class scientists to join the Learned Systems Group to apply machine learning and foundational models to database system challenges. Projects may include Amazon Q Generative SQL, AI-driven cluster scaling, cluster pool optimization, or autonomics. You will build prototypes, innovate on representation learning, and collaborate closely with customers and academic communities.

Key responsibilities:

• Design and develop end-to-end AWS database experiences using C++ and Python.
• Write technical white papers, create roadmaps, and drive production projects supporting Amazon Science.
• Design new algorithms and models to solve technical problems.

A day in the life:

Work within AWS Utility Computing, supporting services like S3, EC2, and others, with opportunities to engage with AWS customers requiring specialized security solutions.

About AWS:

We value diverse experiences and encourage candidates to apply even if they do not meet all qualifications. AWS is the leading cloud platform trusted worldwide, committed to innovation and inclusion.

Why AWS?

We foster a culture of curiosity, inclusion, mentorship, and work-life balance, aiming to be Earth’s Best Employer.

About the team:

Our team focuses on innovative ML initiatives in database systems, with publications available for review.

BASIC QUALIFICATIONS:

• Enrolled in or completed a PhD in engineering, computer science, machine learning, robotics, operations research, statistics, mathematics, or a related field.
• Experience with patents or publications at top-tier conferences or journals.
• Proficient in Java, C++, Python, or related languages.
• Knowledge in algorithms, data structures, parsing, optimization, data mining, parallel/distributed computing, high-performance computing.
• Experience with relational database internals (query execution, scheduling, performance optimization).

PREFERRED QUALIFICATIONS:

• Experience with Unix/Linux.
• Professional software development experience.
• Experience in building machine learning models or algorithms for business applications.