Working Student Machine Learning Engineering (f/m/d)
Summary
Working student role focused on account security systems for fraud and hacking detection. You will develop ML features and high-performance inference services using Python, PySpark, and Kubernetes while monitoring systems with Grafana and Prometheus.
With our strong brands GMX, WEB.DE and mail.com and over 42 million active users, we are the leading email and communications platform in Germany, Austria and Switzerland. From this strong market position, services and apps are developed that simplify users' digital lives - from office tools and cloud solutions to personal ID management.
Your Tasks
As part of a team of analysts, data scientists, and software developers, you will work on account security systems for the detection and classification of hacking attacks, abuse, and fraud involving our accounts.
Your main areas of focus will be the development, testing, deployment, and monitoring of:
- Filter queries and transformation processes that calculate relevant metrics and ML features from billions of events.
- High-performance machine learning inference services.
In the process, you will learn or deepen your knowledge of:
- PySpark, SQL/Trino
- NumPy, Pandas
- GitLab pipelines, Kubernetes
- Grafana, Prometheus
Your Profile
You are currently pursuing a degree, ideally with a focus on Computer Science, Data Science, or a related field, and you see yourself reflected in the following qualities? If so, we look forward to receiving your application!
Additionally, we are looking for:
- Commitment, curiosity, and a strong willingness to learn.
- Very good software development skills, particularly in Python.
- Experience with our standard tools: Git, Linux, Docker.
- Good English skills; German is a plus.
Our Benefits
🏢 Lived corporate culture: Flat hierarchies, a culture of respect and appreciation, signatories of the Diversity Charter, open communication and no dress code
🎓 Wide range of further training: LinkedIn Learning, language courses, internal and external training opportunities, talent development programs, conferences and mentoring
❤️ Active health care: Wellpass, health days, family & care support services, discounts at fitness centers, mental health first responder, fresh fruit and drinks for free
🚝 Mobility: Subsidy for the job ticket
💻 Flexible working models: Up to 2 days/week home office, flexible working hours up to 20 hours per week or up to 40 hours during your lecture-free period
💰 Financial benefits: Corporate benefits and various partner discounts
💵 Hourly wage: Bachelor: 14.00€ / Master: 16.00€ + 15% extra pay per working hour
🎉 Events: Summer and winter parties, sports tournaments and team events
Skills
As published by greenhouse · 13 questions
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter
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- Street / Number
- ZIP Code
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- Which university do you study at?
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- Nationality:
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- Do you agree with the terms below?
- Do you agree to your application being forwarded to other internal departments?
Attachments (1)
- Certificate of enrollment
