About the job
As Senior Engineering Manager for Safety AI Systems at Roblox, you'll lead technical efforts and manage a team of experienced engineers to develop innovative AI solutions for multimodal content safety. You’ll oversee machine learning systems, constructing multimodal model architectures, improving data quality, training pipelines, and model performance to address challenges like real-time multi-verse content understanding and advanced moderation with large vision language models, spanning avatars, images, videos, audios, text, code / data models, and their composites.
Responsibilities
Own the vision, technical direction, and execution of machine learning solutions for the Multimodal Safety AI system, ensuring these systems effectively detect and prevent harmful content at scale.
Lead and grow a high-performing team of ML engineers, fostering a culture of innovation, technical excellence, accountability, and inclusivity, while mentoring and developing talent.
Break down ambitious long-term goals into an actionable, iterative roadmap – delivering continuous improvements in stages and driving tangible value at each step.
Architect and guide the development of large-scale machine learning models with innovative architectures, ensuring they achieve high quality and are production-ready.
Drive alignment on complex technical decisions across multiple teams (within and beyond the Safety org), demonstrating empathy and building consensus among diverse stakeholders.
Collaborate cross-functionally with Product, Data Science, Policy, Design, and Operations partners to define and prioritize the machine learning roadmap for multimodal safety initiatives, ensuring alignment with broader Safety and Roblox objectives.
Stay ahead of emerging trends in AI/ML and content moderation techniques, continuously innovating our safety approaches to anticipate new challenges.
Qualifications
Minimum
5+ years of experience building large-scale machine learning systems in production environments.
Proven track record of designing, developing, and launching ML models from scratch into production.
2+ years of hands-on experience with vision language models or other foundation model technologies.
Expertise in solving complex ML modeling, data, and infrastructure challenges – with a focus on maintaining high quality and velocity at scale.
Ability to thrive in ambiguity: you excel at bringing clarity and direction to undefined or open-ended problem spaces.
Demonstrated success collaborating across functions (e.g. Product, Design, Data, Research), working together to drive meaningful business and user impact.
Strong product sense: able to establish clear success metrics and craft strategic roadmaps to achieve those goals.
High emotional intelligence: adept at resolving conflicts, mentoring engineers, and nurturing the growth of your team members.
Experience with modern microservice architectures and distributed systems programming paradigms (e.g. cloud services, scalable data pipelines).
Hands-on to dive into code/architecture and guide technical discussions when needed, in addition to high-level planning.
Preferred
No preferred qualifications listed.