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Roblox

Senior Machine Learning Engineer - Economy ML

Roblox is hiring a Senior Machine Learning Engineer - Economy ML in San Mateo, United States. It pays $260k-$313k a year and Level rates it ; you can apply on Roblox.

Level's read on this job

  • Builds AI ●●●● is how Level rates this machine learning engineer role: the job is building AI systems.
  • Pay on this posting starts 30% higher than the typical machine learning engineer posting on Level.
  • The posting mentions visa sponsorship.
  • The posting mentions PyTorch among its tools and skills.
  • Roblox has 267 other open roles on Level.

AI in this role

pytorch

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.

The Economy ML team is building the machine learning backbone for Roblox’s virtual economy—from intelligent pricing and personalized storefronts to dynamic layout optimization and avatar content understanding. We partner closely with Marketplace, Payments, and Developer Monetization to deliver ML systems that drive long‑term value across engagement, retention, and creator earnings.

As a Senior Machine Learning Engineer on the team, you will build models that power ranking, personalization, pricing, and optimization across Roblox’s economic surfaces, including Marketplace, Developer Monetization, and Payments. Your work will directly shape how users discover virtual items, how creators earn, and how the platform grows sustainably.

You Will:

  • Design and iterate on modern retrieval, ranking, and generative recommendation models (e.g., transformer-based sequential models over user behavior) that personalize item and widget recommendations across the Marketplace and other shopping experiences.
  • Make these models efficient to train and serve at scale: choose architectures and modeling approaches with compute, latency, and cost budgets in mind, and partner with ML infrastructure engineers on distributed training and production serving.
  • Work backwards from ambiguous product problems and opportunities to design and ship end‑to‑end ML solutions across Economy surfaces, owning the full lifecycle: data and feature exploration, modeling, evaluation, and production deployment on Roblox’s ML platform.
  • Develop models and policies that optimize pricing, conversion, and revenue while balancing ecosystem health, payer experience, and creator success.
  • Design and run robust experiments (A/B tests and multi‑cell experiments), tying your work to core metrics such as engagement, bookings, and creator earnings.
  • Keep models healthy in production: set up monitoring for data and prediction quality, catch drift and regressions early, and help define the team’s on-call practices for ML services.
  • Partner cross‑functionally with Product, Backend, Data Science, Design, and other Marketplace / Economy teams to define roadmaps, requirements, and success metrics for ML‑driven features.
  • Contribute to the technical direction of the Economy ML team: help shape our modeling roadmap, experimentation strategy, and approaches to long‑term reward optimization across the economy.
  • Mentor other engineers through design reviews, code reviews, and hands-on guidance, helping raise the technical bar of the broader Economy organization.

You Have:

  • 3+ years of industry experience building recommendation, search, or ranking systems for a high-scale product. Experience with pricing or content understanding is a plus.
  • Deep, hands-on expertise in modern recommender architectures (e.g., sequence models of user behavior, multi-task ranking, large sparse embeddings) and in making them efficient to train and serve: comfortable with multi-GPU training and with the tradeoffs between model quality, latency, and cost. Experience applying LLM or multimodal techniques to recommendation is a plus.
  • Fluent in the ML lifecycle: Comfortable taking a problem from messy data and product ambiguity through modeling, evaluation, and stable production deployment, with strong coding skills in Python and PyTorch.
  • You think in terms of impact on users, creators, and the business, and you can reason clearly about how model choices affect metrics like LTV, engagement, conversion, and creator earnings.
  • You are comfortable designing experiments, diagnosing metric movements, and iterating quickly while maintaining statistical rigor and healthy guardrails for the ecosystem.
  • You enjoy working closely with engineers, product managers, data scientists, and designers across Marketplace, Payments, and Developer Monetization, and you can drive alignment in complex, multi‑stakeholder environments.
  • You take a long‑term view of the Roblox economy, are comfortable challenging assumptions, and can balance quick wins with foundational investments in data, infrastructure, and modeling quality.

For roles that are based at our headquarters in San Mateo, CA: 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. This pay range is subject to change and may be modified in the future. All full-time employees are also eligible for equity compensation and for benefits as described on this page.

Annual Salary Range$260,300—$312,970 USD

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

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.

How we rate this

Senior Machine Learning Engineer - Economy ML at Roblox rates 94 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

PyTorch

Also common in machine learning engineer jobs at this level

Pay

This job starts at
$260k
Typical machine learning engineer job
$200k

This posting starts 30% above the typical machine learning engineer job. See machine learning engineer jobs

Questions you could be asked

  1. What's a project where you used PyTorch hands-on?
  2. How would you decide a model or AI system is ready to ship?
  3. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: PyTorch. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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