8 beste Stellen als machine learning engineer in rheinland pfalz – aktuell auf Personalsuche

Python Software Engineer - Machine Learning Systems (m/f/d)
CUJU —Frankenthal
- Homeoffice
- Forschungserfahrung
- AWS
- Machine Learning
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TRENDVIEW GMBH —Koblenz
- CRM-Software
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KI Prompt Engineer/AI Consultant (m/w/d) – 100% remote
mycareernow GmbH —Speyer
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- PC-Kenntnisse
- Künstliche Intelligenz
- Weiterbildungsprogramme
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Quereinstieg als Prompt Engineer (m/w/d) – 100% remote
mycareernow GmbH —Ludwigshafen am Rhein
- Ab 50.000 € pro Jahr
- Teilzeit
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- PC-Kenntnisse
- Künstliche Intelligenz
- Weiterbildungsprogramme
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ITS People —Sprendlingen
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- Azure
- Englisch
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- Weiterbildungsprogramme
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mycareernow GmbH —Frankenthal
- Ab 50.000 € pro Jahr
- Teilzeit
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machine learning engineer jobs near rheinland pfalz

Python Software Engineer - Machine Learning Systems (m/f/d)

CUJU
Frankenthal

Direkt bewerben

Details zur Stelle

Qualifikationen

CI/CD
Kubernetes
Git
Forschungserfahrung
AWS
Docker
Machine Learning
GitHub
APIs
GitLab
Python

Vollständige Stellenbeschreibung

Location: Hybrid/ Remote (Germany-based)

Start: ASAP | Languages: Fluent English

Note that we cannot provide any visa or relocation support.

Make the Unseen seen! Our goal is to reinvent scouting in football and build the #1 global scouting platform for identifying and developing talent. With the help of modern AI technology, CUJU enables every young football talent to be seen – regardless of origin, gender, or social background. We create fair opportunities and transparent pathways into professional sports. Our platform connects athletes, clubs, and organizations worldwide to rethink scouting – data-driven, objective, and mobile. Together, we are shaping the next generation of global talent scouting.

Your Mission:

As a Python Software Engineer – Machine Learning Systems at CUJU, you will help us build, scale, and maintain production-grade ML systems.

This is not a research role. We already have a live product and real users. Our focus is on reliable, scalable, and maintainable ML systems that deliver value in production. If you prefer working in notebooks over building and operating production systems, this role is not a fit.

You’ll work across the full ML lifecycle from integrating models into products to improving pipelines, infrastructure, and system performance. We expect you to treat models as software components, not experiments.

Tasks

What You’ll Work On:

Design, build, and maintain production ML systems and pipelines
Write clean, testable, and maintainable Python code
Deploy and operate models in production (APIs, batch jobs, real-time systems)
Work hands-on with AWS infrastructure to build scalable systems
Use distributed systems (Ray) for large-scale workloads and model serving
Containerize and deploy services using Docker (Kubernetes is a plus)
Improve and maintain CI/CD pipelines for ML workflows
Ensure robust testing, monitoring, and reliability of ML systems
Contribute to improving system architecture, performance, scalability and cost efficiency
Treat modeling as part of software engineering—not a separate activity

Requirements

What You Bring:

We’re looking for engineers with 4+ years of experience in software engineering, including hands-on experience building, deploying, and operating ML systems in production. Experience limited to research or notebook-based work is unfortunately not sufficient for this role.

Strong programming skills in Python (clean architecture, testing, modular design not just scripts).
Proven experience building and operating systems on AWS (preferred) or strong experience with a comparable cloud platform
Experience with Ray (or similar distributed compute frameworks) is a strong plus. We actively use Ray in production for distributed workloads and model serving.
Experience with:
Git (collaborative workflows, code reviews)
CI/CD pipelines (GitHub Actions, GitLab CI, etc.)
Testing (unit + integration — not optional)
Experience with Docker (Kubernetes or similar is a strong plus)
Hands-on experience with production infrastructure (CI/CD, monitoring, logging, deployments)

Nice to Have:

Experience with computer vision
Experience training and evaluating ML models
Familiarity with MLOps tooling
Experience optimizing models for latency, scale, and cost

Benefits

Work on a live product with real-world impact
Build end-to-end ML systems, not just models
Operate in an environment that values engineering excellence
Have real ownership over systems in production
Significant influence on CUJU’s growth, product strategy, and industry-leading innovation.
Competitive compensation, remote flexibility, and a vibrant, international working environment.
Direct collaboration with top-tier football clubs, industry experts, and an ambitious cross-functional team.
Significant influence on CUJU’s growth, product strategy, and industry-leading innovation
Short decision-making paths – direct communication, quick decisions, and close collaboration with management
Personal development – individual learning opportunities and room to grow beyond yourself
Diverse benefits – e.g. 30-day vacation, competitive compensation, corporate benefits, and moree environment,

Your Impact:

You deliver ML systems that are reliable, scalable, and used in production
You proactively improve code quality, infrastructure, and system design
You take full ownership of systems, including failures and fixes
You bring an engineering-first approach to all ML work

️ Is this your next big play?

Are you passionate about sports, communicative, and eager to actively shape the future of sports? Then we look forward to your application!

Please send us your CV directly via the application link for JOIN.

Please acknowledge that we can only accept applications online through our recruiting software due to GDPR. Thank you!

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