AI/ML Engineer

About the role

WHO WE ARE

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, Melotech has raised more than $16M from Drive Capital and Europe’s leading VCs: Cherry Ventures, Speedinvest and Global Founders Capital, 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