> Markdown version of [/jobs/ext/3831035-ai-ml-engineer](https://www.wearedevelopers.com/jobs/ext/3831035-ai-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# AI/ML Engineer

- **Company:** Melotech
- **Location:** Berlin, Germany (Remote available)
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Cloud Computing, Monitoring of Systems, Python (Programming Language), Machine Learning, Tensorflow, Systems Integration, System Availability, Kubernetes, Information Technology, Low Latency, Machine Learning Operations, Software Version Control, Docker
- **Published:** October 19, 2026
- **Apply:** https://www.adzuna.de/details/5932428107

## About the Role

* Degree in Computer Science, Machine Learning, Mathematics, Engineering, or related technical field
 * 3+ years of hands-on ML engineering experience building production systems at Big Tech companies, high-growth startups, or media/entertainment platforms
 * Expert-level proficiency in Python, ML frameworks, and cloud platforms
 * Extensive experience with MLOps tools and practices including Docker, Kubernetes, model versioning, and monitoring systems
 * Proven track record deploying and scaling ML models in production environments with high availability requirements
 * Self-directed approach with ability to architect complex systems independently while collaborating across technical teams
 * You thrive in a fast-paced and performance-oriented environment
 * Colleagues would describe you as hard-working, ambitious and persistent
 * You're obsessed with music, video or social media

## Description

As our ML Engineer, you'll be the technical backbone powering our content platform. You'll tackle the critical questions: How do we build ML systems that scale to millions of users while maintaining low latency? What's the optimal architecture for training and deploying models that understand cultural trends in real-time? And how do we leverage cutting-edge models to enhance creative processes while preserving quality? Working fully autonomously alongside our founder and the team, your answers to these questions will directly influence our company's success. On a typical day, your tasks may include:

 * Building and deploying production ML models for within our content and product ecosystem
 * Designing scalable ML infrastructure and pipelines that handle massive media datasets
 * Implementing inference systems for content optimization across multiple verticals
 * Fine-tuning and deploying multimodal AI systems using MLOps best practices
 * Collaborating with data science teams to transition research models into production-ready systems
 * Optimizing model performance for cost efficiency while maintaining accuracy and speed requirements
 * Integrating ML capabilities into existing platforms and building APIs for seamless model consumption