Roblox is looking to solve the problem of creating a safe and civil online community by advancing large-scale AI systems that strengthen platform safety and integrity.
Requirements
- 6+ years of experience designing, building, and deploying large-scale machine learning systems in production environments.
- A graduate degree or equivalent experience in Computer Science, Engineering, or a related technical field.
- Hands-on experience with fine-tuning VLMs, LLMs, or large multimodal models to improve model quality, safety, and performance is a plus.
Responsibilities
- Design, build, and own critical components of the AI systems that powers safety data needs, with a focus on usability, reliability, scalability, and performance.
- Implement robust pipelines for curating high-quality multimodal datasets used to train and evaluate ML models and human-in-the-loop systems that enable safe and compliant AI.
- Advance our AI systems infrastructure by developing strong frameworks for data quality, synthetic data generation, and synthetic labeling.
- Partner with cross-functional teams of engineers, product managers, policy experts, and safety specialists to to deliver scalable data and AI solutions to power next-generation safety systems.
- Shape and influence the company’s data culture and best practices, building foundational systems from scratch and driving impact rapidly.
- Stay current with emerging technologies and push forward innovation in data and AI to enhance user and platform safety.
Other
- Strong communication skills and a collaborative, solution-oriented approach to problem solving.
- Data & System Oriented: You understand that robust data and systems are the foundation of any production applications, and you design infrastructure for scale, correctness, and reliability.
- Collaborative: You thrive in cross-functional teams, partnering effectively with Product and Engineering to solve complex challenges.
- Curious & Creative: You enjoy tackling hard problems, exploring new technologies, and driving continuous improvements in both systems and workflows.
- Impact Driven: You focus on outcomes - prioritizing product impact, reliability, and measurable success over code volume or complexity.
