Distinguished Machine Learning Engineer

About the role

Every day, tens of millions of people come to Roblox to explore, create, play, learn, and connect with friends in 3D immersive digital experiences- all created by our global community of developers and creators. At Roblox, we're building the tools and platform that empower our community to bring any experience that they can imagine to life. Our vision is to reimagine the way people come together, from anywhere in the world, and on any device. We're on a mission to connect a billion people with optimism and civility, and looking for amazing talent to help us get there. A career at Roblox means you'll be working to shape the future of human interaction, solving unique technical challenges at scale, and helping to create safer, more civil shared experiences for everyone. As a Distinguished Machine Learning Engineer/Technical Director in the Safety organization at Roblox, you will drive the overall technical vision and execution for all machine learning initiatives focused on maintaining the safety and civility of our users. Our industry-leading safety features ensure Roblox remains a safe and inclusive environment for our community to express themselves creatively and share experiences without fear. The Safety org is the reason why Roblox is the safest place on the internet, protecting users You will provide technical leadership on AI/ML efforts for Trust and Safety as the Roblox platform scales to serve different age groups and geographic locations.

Key facts

What you'll do

Provide technical leadership on machine learning initiatives for safety and trust and safety systems as the Roblox platform scales to serve different age groups and geographic locations.

Own the technical direction and implementation of machine learning solutions for safety-related systems to ensure they remain effective and scalable.

Lead and mentor other engineers, fostering a culture of technical excellence and inclusivity within the safety engineering organization.

Break down long-term product requirements into iterative deliverable stages, ensuring continuous improvement and alignment with safety objectives.

Craft and build large-scale machine learning models with billions of parameters, ensuring they are production-ready and performant at global scale.

Facilitate challenging technical decisions across multiple teams, demonstrating empathy and finding common understanding to advance safety priorities.

Collaborate with cross-functional teams to define and prioritize the machine learning roadmap, balancing innovation, risk, and execution constraints.

Analyze complex data problems and design model architectures that can handle massive datasets while maintaining reliability and safety standards.

Partner with product and policy teams to translate safety requirements into machine learning features and evaluation frameworks.

Drive the adoption of best practices in model development, testing, and deployment to ensure robustness and compliance.

Contribute to the development and enhancement of industry-leading safety features that protect users and preserve the integrity of the platform.

Explore emerging techniques in NLP and computer vision to improve content moderation, detection, and prevention of harmful experiences.

Requirements

10+ years of experience delivering and improving large-scale machine learning systems in production environments.

Proven expertise in creating and launching machine learning models from scratch, including data strategy, feature engineering, and model selection.

Ability to handle data problems, train models with large datasets, and ensure system reliability at scale across diverse user segments.

Experience with distributed systems, data architecture, and model extraction techniques to support high-throughput safety workflows.

Strong programming skills and willingness to be hands-on when necessary, including debugging complex model behaviors and integrating components.

Prior experience in a leadership role with a technical focus, including mentoring engineering teams and guiding technical direction.

Knowledge of safety system maintenance and evolution at scale, including monitoring, alerting, and iterative improvement processes.

Commitment to fostering a diverse and inclusive workplace where everyone feels valued, supported, and empowered to contribute.

Nice to have

Prior experience in NLP or computer vision is preferred for this role.

Familiarity with maintaining and evolving safety systems at scale, including moderation pipelines and policy enforcement mechanisms.

Knowledge of cutting-edge ML technologies, including large language models and their applications in trust and safety.

Practical notes

This is a full-time position based in San Mateo, California, United States.

Candidates must be authorized to work in the United States without sponsorship for this role.

Travel is not expected for this role.

Visa sponsorship is not available for this position.

The position is eligible for equity compensation as part of the total rewards package.

All full-time employees are eligible for benefits as described on the total rewards page.