Melotech is revolutionizing media and entertainment by creating art through technology, and needs to build ML systems that scale to millions of users while maintaining low latency, understand cultural trends in real-time, and enhance creative processes while preserving quality.
Requirements
- 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
Responsibilities
- 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
Other
- 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
- 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
