Melotech AI/ML Engineer Intern Berlin | Media AI VC-Backed
| Company | Melotech — media & entertainment AI; 3B+ minutes consumed worldwide in 24 months; backed by Cherry Ventures, Speedinvest, GFC + angels from Spotify, Blackstone, KKR |
| Role | AI/ML Engineer Intern |
| Location | Berlin listed; company works remotely with global offsites |
| Start | Rolling hire — ASAP |
| Focus | Production ML at scale, multimodal AI, MLOps, inference for content optimization, ML APIs |
| Comp | Competitive pay + equity (per listing); early-employee impact |
| Stack | Python, ML frameworks, cloud platforms; production ML infrastructure |
Overview
Melotech creates art through technology for media and entertainment. In 24 months their work has been heard/watched for over 3 billion minutes worldwide. Founded by Soheil Mirpour and backed by Cherry Ventures, Speedinvest, GFC, and angels from Spotify, Blackstone, and KKR.
As ML Engineer Intern you’ll be the technical backbone of the content platform — building/deploying production models, designing scalable ML infra for massive media datasets, implementing inference for content optimization, fine-tuning multimodal systems with MLOps practices, and turning research models into production-ready systems. Work is highly autonomous alongside the founder and early team. Still in stealth — full business detail comes during the process.
Key Requirements
- Education: Pursuing CS, ML, Maths, Engineering, or related technical field.
- Experience: Hands-on ML engineering building production systems (Big Tech, high-growth startups, or media/entertainment platforms).
- Skills: Strong Python, ML frameworks, and cloud platforms; able to architect complex systems independently while collaborating.
- Mindset: Fast-paced, performance-oriented; hard-working, ambitious, persistent; obsessed with music, video, or social media.
- What you’ll ship: Production ML models; scalable pipelines; multimodal fine-tuning/deploy; cost/latency optimization; APIs for model consumption.
- Process (≈1 week if you move fast): Take-home case → 90-min case interview → online assessment → founder interview → team interview → offer.
