Senior Machine Learning Engineer, User Behavior

Why User Behavior?

You will build the proactive detection and behavioral intelligence systems that fundamentally shift how Roblox responds to unsafe behavior, from reactive punishment to early, education-first intervention. You will own the ML foundation for a new capability at Roblox: identifying users at risk of becoming chronic violators before they escalate, and powering the adaptive consequence systems that give them a real chance to change.

Responsibilities

• Define and Own the ML Vision: Define and lead the multi-year ML vision, architectural strategy, and execution that identify casual violators early before they escalate, and operate reliably under real-world policy and precision constraints.
• Own Behavioral Prediction Models: Develop and maintain production ML models that translate user behavioral signals into actionable risk intelligence, enabling earlier and more targeted interventions.
• Build the ML Foundation from Scratch: Design the user feature store, training pipelines, and model evaluation infrastructure that underpin behavioral ML at Roblox.
• Instrument Experiments for Causal Validity: Partner with XFN stakeholders to ensure A/B tests on intervention variants have proper random assignment and instrumentation for future causal model training. This data cannot be retroactively collected.
• Drive End-to-End Product Development: You will not just model; you will build. You will work cross-functionally to construct datasets from scratch where none exist, build labeling pipelines, and ship solutions to various product surfaces.
• Ship Code, Not Just Models: Expect to own end-to-end delivery, building and operating ML pipelines from training and offline evaluation through production serving. You will integrate your models directly into the stack alongside SWE.

Requirements

• 5+ years of experience building and shipping production ML systems at scale.
• Hands-on experience with ML classification at scale, including traditional ML models, sequence modeling on user-event data, and/or LLM-based approaches, with strong intuition for model evaluation on real-world data.
• Proficiency designing and maintaining feature pipelines and feature stores for behavioral or event-driven data.
• Experience building embedding-based retrieval systems (ANN / vector search) in production.
• Experience building and operating end-to-end ML pipelines: training, offline evaluation, A/B experiment hooks, and production serving infrastructure.
• Strong understanding of ML experiment design, including training data validity, label quality, recall/precision tradeoffs under constrained thresholds, and causal inference fundamentals.
• Nice to have: experience in Trust & Safety, user behavior modeling, or user understanding (e.g., churn prediction, engagement modeling, risk scoring); familiarity with uplift/causal ML; sequence models on user-event data.

Qualifications

• A Visionary Architect: Capable of synthesizing complex business and safety goals into a clear, compelling, and actionable technical strategy.
• A Pragmatic Builder: You are scrappy and impact-oriented. You view undefined data and messy systems as opportunities to build structure rather than blockers to progress.
• Comfortable with Ambiguity: You thrive in undefined or open-ended problem spaces, providing structure, clarity, and decisive direction to your teams.
• An Inspiring Leader: Passionate about developing the next generation of technical leaders, managers, and engineers.
• An Executive Communicator: Highly effective at communicating complex technical concepts to both engineering teams and non-technical executive leadership.
• Committed to Ethical AI: Dedicated to building ML systems that are fair, transparent, and operate with the utmost responsibility toward user safety and platform civility.

Benefits

• The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range.
• Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Pay

• The starting base pay for this position is as shown below. The actual base pay is dependent upon a variety of job-related factors such as professional background, training, work experience, location, business needs and market demand. Therefore, in some circumstances, the actual salary could fall outside of this expected range.

Schedule

• Roles that are based in an office are onsite Tuesday, Wednesday, and Thursday, with optional presence on Monday and Friday (unless otherwise noted).

Company Information

• Roblox provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.
• Roblox also provides reasonable accommodations to candidates with qualifying disabilities or religious beliefs during the recruiting process.
• For US based roles only, please note the Company may not be able to employ candidates for this role who have United States work authorization related to certain U.S. visa categories, or support future H-1B sponsorship at this time.