About the job
About Us
At Melotech, we are transforming the media and entertainment landscape by merging art with technology, crafting experiences that resonate with audiences globally. In just two years, our innovative projects have garnered over 3 billion minutes of engagement worldwide.
Founded by visionary entrepreneur Soheil Mirpour, we are proudly supported by leading venture capitalists including Cherry Ventures, Speedinvest, and GFC, along with esteemed angel investors from top firms such as Spotify, Blackstone, and KKR.
Your Role
As a Machine Learning Engineer at Melotech, you will be the pivotal force driving our content platform. You will face essential challenges: How can we construct ML systems that efficiently serve millions while ensuring low latency? What is the best architecture for developing and deploying models that interpret cultural trends instantaneously? How can we harness advanced models to enrich creative processes without compromising quality? Your autonomous work will directly shape our success, collaborating closely with our founder and team. Daily responsibilities may include:
- Building and implementing production-grade ML models within our content ecosystem.
- Designing scalable ML infrastructure and pipelines to manage extensive media datasets.
- Creating inference systems for content optimization across various sectors.
- Tuning and deploying multimodal AI systems utilizing MLOps best practices.
- Partnering with data science teams to transition research models into production-level solutions.
- Enhancing model efficiency for cost-effectiveness while ensuring accuracy and rapid response times.
- Integrating ML functionalities into existing platforms and developing APIs for streamlined model access.
Your Profile
You are an ML engineer focused on production who connects cutting-edge technology with scalable systems. Your expertise lies in constructing resilient ML infrastructures that support real-world applications at scale. You thrive in dynamic environments where your technical choices significantly influence business outcomes and user experiences. Your qualifications typically include:
- A degree in Computer Science, Machine Learning, Mathematics, Engineering, or a related field.
- 3+ years of practical ML engineering experience developing production systems at leading tech companies, high-growth startups, or in the media/entertainment sector.
- Strong grasp of machine learning frameworks and libraries.
- Experience with cloud platforms and deployment strategies.
- Proficiency in programming languages such as Python, Java, or C++.
