AI/ML Engineer arbeitnow Melotech Berlin · 10/20/2026

Primetime; Berlin; Hybrid; EUR 90,000 - 110,000; Full time

Benefits offered by this job

Equity

Remote work

Job summary

Melotech is reshaping media and entertainment through AI-powered content platforms. As an ML Engineer, you’ll build scalable models and infrastructure, deploying them for millions of users with low latency and high availability.

You’ll work closely with our founder and team, shaping architecture and product impact from day one. You’ll implement end-to-end ML workflows, from data pipelines to productionized inference, while embracing cutting-edge models to enhance creativity without compromising

Qualifications

• Degree in Computer Science, ML, Math, Engineering, or related field.
• 3+ years building production ML systems at scale.
• Expert Python, ML frameworks, and cloud platforms.
• Experience with Docker, Kubernetes, model versioning, monitoring.

Responsibilities

• Build and deploy production ML models within our content platform.
• Design scalable ML infrastructure and data pipelines.
• Implement efficient inference across products.
• Fine-tune and deploy multimodal AI systems with MLOps best practices.
• Collaborate with data science to move research models to production.
• Optimize model performance for cost, speed, and accuracy.
• Expose ML capabilities via APIs for easy model consumption.

Skills

Python

ML frameworks

Cloud platforms

MLOps

Production ML

APIs

Model versioning

Monitoring

Education

BSc in CS/Math/Engineering

Tools

Docker

Kubernetes

Job description

Melotech is revolutionizing media and entertainment. We create art through technology for humans to enjoy. In just 24 months, our work has been heard, watched and loved for over 4 billion minutes worldwide.
Founded by entrepreneur and investor Soheil Mirpour, we are backed by top VCs Cherry Ventures, Speedinvest and GFC, alongside world-class angels from firms such as Spotify, Blackstone and KKR.

What you will do

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 right architecture for training and deploying models that learn from real time data? 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 within our content and product ecosystem
• Designing scalable ML infrastructure and pipelines that handle massive media datasets
• Implementing efficient inference systems across our products
• 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

Who you are

You're a production-focused ML engineer who bridges the gap between cutting-edge tech and scalable systems. Your expertise lies in building robust ML infrastructure that powers real-world applications at scale. You thrive in fast-paced environments where your technical decisions directly impact business outcomes and user experiences. Typically, your profile will look like this:

• 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

What makes this exciting

You are one of the first employees of an ambitious team, changing the world of media and entertainment. Being early means every decision you make shapes our trajectory. You're not a cog in the machine but the captain of your own ship, rewarded for performance and respected for leadership. Flat hierarchies mean that your voice matters, your ideas get implemented, and your impact is immediate.
We pay competitive salaries and make you an owner of the business with equity. We work remotely to give you complete freedom over your life, while meeting regularly around the world for global offsites where we strategize, bond, and push boundaries together.

What the process will look like

We hire on a rolling basis. Earliest starting date is always ASAP.
Once you begin our process, you can progress from start to offer within a week, depending on how quickly you can move through each stage:

• Take-home case study: Real-world project - showcase your skills and working style
• Case interview: 90-minute case discussion - getting to know you & present and debate your results with a team member
• Online assessment: Motivational questionnaire and aptitude test - are you made for the job?
• Founder interview: 90-minute interview with our CEO - going deep on all topics
• Team interview: Individual or group interview with other team members - depending on position
• Offer, contract signing and onboarding

Note: As we are still in stealth, you will learn more about Melotech as you progress through the stages. By the end of the Founder interview, you will have a full grasp of our business and the details of your role.

This overview was written from the original listing to help you understand the role. Always confirm the specifics on the employer’s application page.