Principal Machine Learning Engineer, Content Safety

Roblox Roblox · Consumer · San Mateo, CA · Software Engineering

Principal Machine Learning Engineer focused on Content Safety at Roblox. This role involves defining the 3-5 year technical strategy and architectural blueprint for ML-driven content moderation, owning the roadmap for large-scale ML systems to mitigate violative UGC content. The engineer will also be involved in building datasets, auto-labeling pipelines, and shipping solutions, with 30-40% of time dedicated to backend and integration work. Requires expertise in Computer Vision and/or Vision-Language Models, and architecting scalable, real-time ML inference services.

What you'd actually do

  1. Define and lead the multi-year technical vision, architectural strategy, and execution for machine learning solutions in Content Safety, ensuring these systems proactively and effectively detect and mitigate violative content at massive scale.
  2. Collaborate with executive-level Product, Data Science, Policy, and Operations leaders to define and prioritize the strategic machine learning roadmap, influencing product strategy and demonstrating the impact of ML on user trust and safety outcomes.
  3. Oversee the adoption and safe deployment of innovative machine learning techniques (e.g., transfer-learning, self-supervised learning, quantization, LoRA, distillation).
  4. You will work cross-functionally to construct datasets from scratch where none exist, build auto-labeling pipelines, and ship solutions to solve novel technical problems.
  5. Expect to spend roughly 30-40% of your time on backend and integration work. You will be responsible for integrating your work into the production stack, leveraging modern AI coding tools (e.g., Cursor) to accelerate velocity and handle infrastructure complexity

Skills

Required

  • 8+ years of experience designing, developing, and operating large-scale, high-impact machine learning systems in a production environment.
  • Proven track record of successfully setting the long-term technical direction for an entire ML domain.
  • Deep expertise in advanced ML architectures and techniques, including Computer Vision (CV) and/or Vision-Language Models (VLMs)
  • Expertise in architecting scalable, real-time ML inference services and robust data pipelines.
  • Demonstrated success in leading and resolving high-stakes, cross-functional conflicts and technical disagreements.
  • Exceptional product sense and strategic planning ability.

Nice to have

  • transfer-learning
  • self-supervised learning
  • quantization
  • LoRA
  • distillation
  • modern AI coding tools (e.g., Cursor)

What the JD emphasized

  • Define and Own the Technical Vision
  • multi-year technical vision
  • architectural strategy
  • execution
  • massive scale
  • long-term technical direction
  • scaled production impact
  • real-time ML inference services
  • robust data pipelines

Other signals

  • ML for content moderation
  • proactive moderation
  • mitigate violative UGC content
  • massive scale ML systems
  • real-time ML inference services