Machine Learning Engineer

Code Compass ?; Berlin; Hybrid; EUR 70.000 - 110.000; Vollzeit

Benefits dieser Stelle

Hybrid work options

Professional development support

Social activities

Zusammenfassung

Code Compass is a technology-driven organisation developing intelligent software solutions that leverage AI, automation, and data processing to solve complex business challenges. This role focuses on taking cutting-edge ML research into production, with tangible real-world impact.

You will develop, train, and deploy computer vision and generative AI models, collaborate with engineering and product teams, and contribute to robust ML infrastructure within a hybrid work setup.

Qualifikationen

• Hands-on experience building computer vision and generative AI models.
• Proficiency in deploying ML systems to production environments.
• Strong Python development skills and modern ML tooling.
• Ability to collaborate with cross-functional teams on AI solutions.

Aufgaben

• Develop, train, and optimise ML models for computer vision and generative AI.
• Build and deploy scalable ML solutions into production environments.
• Design automation to reduce manual effort and boost efficiency.
• Monitor model performance and improve reliability and accuracy.
• Collaborate with engineering, product and operations to deliver AI-driven results.
• Research new AI technologies and assess their business fit.
• Contribute to production-grade ML infrastructure and workflows.

Kenntnisse

Python

PyTorch

TensorFlow

Computer Vision

Generative AI

Diffusion Models

GANs

Image Processing

Docker

Cloud Platforms

Production ML Systems

Automation

AI Workflows

Tools

Docker

Cloud Platforms

Jobbeschreibung

Our client is a technology-driven organisation developing intelligent software solutions that leverage artificial intelligence, automation, and advanced data processing to solve complex business challenges at scale.

Operating at the intersection of machine learning, software engineering, and product innovation, they are investing heavily in next-generation AI capabilities and expanding their engineering team to support the continued evolution of their platform and services.

This role is ideal for a Machine Learning Engineer who enjoys taking cutting-edge AI solutions from research to production and wants to work on technically challenging projects with tangible real-world impact.

Python, PyTorch, TensorFlow, Computer Vision, Generative AI, Diffusion Models, GANs, Image Processing, Machine Learning, Docker, Cloud Platforms, Production ML Systems, Automation, AI Workflows

About the Role:

• As a Machine Learning Engineer, you will:
• Develop, train, and optimise machine learning models focused on computer vision and generative AI applications
• Build and deploy scalable ML solutions into production environments
• Design automation solutions that reduce manual effort and improve operational efficiency
• Monitor model performance, identify improvement opportunities, and enhance reliability and accuracy
• Collaborate closely with engineering, product, and operational teams to deliver practical AI-driven solutions
• Research emerging technologies and rapidly evaluate their suitability for business applications
• Contribute to the evolution of production-grade machine learning infrastructure and workflows
• Several years of hands-on experience within machine learning and computer vision
• Strong Python development skills with experience using frameworks such as PyTorch or TensorFlow
• Practical experience working with generative AI technologies including diffusion models and GANs
• Understanding of ML deployment, scalability, performance optimisation, and production environments
• Experience with Docker and cloud-based infrastructure
• Knowledge of creative AI tools and visual content workflows
• Experience working with image-based products, digital content platforms, or related industries
• Strong analytical thinking combined with a pragmatic, solution-oriented mindset
• Ability to communicate effectively in an international and cross-functional environment
• Opportunity to work on cutting-edge AI and machine learning technologies
• Highly collaborative and innovative working environment
• Flexible working arrangements with hybrid options
• Exposure to challenging technical problems with real-world impact
• Professional development support, training, and continuous learning opportunities
• Modern working environment with strong team culture and regular social activities

Due to the volume of applications, we may not be able to respond to everyone individually. However, we genuinely appreciate every application and will contact shortlisted candidates directly.