Distinguished Engineer, Machine Learning Systems – Economy
What the posting says
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.
At Roblox, we’re building the tools and platform that empower a global community of creators and developers to build immersive experiences and a dynamic virtual economy. Our Economy ML team sits at the heart of this mission, delivering scalable machine learning systems that power personalization, pricing, search, and content understanding across all Economy surfaces: Marketplace, Developer Monetization, Payments, and Avatar.
We’re looking for a Distinguished Engineer/Technical Director to lead the strategy and technical direction for ML systems, with a focus on large-scale recommendations, infrastructure, and emerging Generative AI applications. You’ll help build the systems that support retrieval, ranking, generative modeling, and LLM-powered personalization, all at massive scale. This role requires deep systems thinking, hands-on ML expertise, and a vision for how traditional ML and GenAI come together to power the future of the Roblox economy.
Why Roblox for ML Systems
AI/ML is a top company priority, with long-term investment.
Real-world scale: Power millions of daily economic interactions across ranking, pricing, fraud, and search.
Full-system ownership: Build and optimize end-to-end ML pipelines; from data ingestion to GPU training to live inference.
Complex surfaces, rich signals: Design systems for 3D content, UGC, avatar metadata, behavioral and economic signals, not just text or images.
Impact meets innovation: Shape the future of the Roblox economy while working on frontier ML infra and GenAI workflows.
You will:
Set the technical direction for ML systems powering core economy experiences: personalization, ranking, generative modeling, and more
Build and evolve infrastructure for training, serving, and evaluating both traditional ML models and Generative AI models (e.g., embedding-based retrieval, transformers, LLM-based workflows)
Partner with GenAI teams to explore multi-modal embeddings, avatar generation, and retrieval-augmented generation (RAG) in economic surfaces
Lead efforts to optimize ML system performance: low-latency serving, efficient GPU training, and cost-aware inference strategies
Guide the development of robust ML pipelines, online feature stores, and experimentation platforms that support both predictive and generative use cases
Collaborate with EMs, tech leads, and product partners to align technical architecture with business priorities
Mentor senior engineers and help establish a strong technical culture across the Economy ML team
Ensure robustness, observability, and scalability of ML systems that power millions of daily economic interactions
Own the architecture behind some of Roblox’s most foundational ML systems
Work across groups at Roblox to advance the state of ML/AI at the company.
Help scale a fast-growing ML organization and define Roblox’s future economy intelligence stack
Solve real-world problems with real user impact, powering millions of personalized, intelligent economic interactions every day
You have:
10+ years of experience in software engineering or ML infrastructure, with a strong focus on large-scale ML systems
Deep expertise in building recommendation systems, ranking infrastructure, or real-time personalization engines
Hands-on experience with Generative AI, such as transformer-based models, LLMs, embeddings, or RAG pipelines
Proven experience with distributed training, model deployment, and GPU-accelerated workflows
Strong understanding of ML system architecture: data pipelines, feature stores, inference optimization, experimentation tooling
Systems-first mindset with strong instincts around scale, cost, performance, and reliability
Track record of leading large technical initiatives and mentoring senior engineers
BS, MS, or PhD in Computer Science, Machine Learning, or a related field
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
$397,460—$455,720 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.
Quality
- + Salary range stated weight 35%
- x Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Based on 102 observation(s).
- + Days open - fineOpen for 54 days so far
- + Reopen count - fineNever reopened
- + Salary range removed after publication - fineSalary range has not been removed since publication
- + Salary range narrowed - fineSalary range has not narrowed since publication
- + Missing/reappear cycles - fineNo missing-then-reappeared cycles observed
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~
#1036522 2026-09-27 22:19 UTCModified
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~
#1043730 2026-09-28 10:25 UTCModified
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2026-09-27T14:43:36-04:00->2026-09-28T02:44:32-04:00
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~
#1054281 2026-09-28 22:26 UTCModified
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~
#1063467 2026-09-29 10:34 UTCModified
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2026-09-28T14:45:00-04:00->2026-09-29T02:44:39-04:00
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~
#1077105 2026-09-29 22:36 UTCModified
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#1088354 2026-09-30 10:37 UTCModified
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2026-09-29T16:09:38-04:00->2026-09-30T02:44:24-04:00
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~
#1099671 2026-09-30 22:37 UTCModified
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#1109355 2026-10-01 10:41 UTCModified
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2026-09-30T14:45:24-04:00->2026-10-01T02:44:38-04:00
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#1118185 2026-10-01 18:47 UTCModified
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2026-10-01T02:44:38-04:00->2026-10-01T14:44:42-04:00
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#1129596 2026-10-02 07:06 UTCModified
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#1140494 2026-10-02 19:24 UTCModified
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2026-10-02T02:44:21-04:00->2026-10-02T14:45:33-04:00
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~
#1159750 2026-10-03 19:33 UTCModified
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2026-10-02T14:45:33-04:00->2026-10-03T14:43:22-04:00
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~
#1167517 2026-10-04 07:47 UTCModified
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2026-10-03T14:43:22-04:00->2026-10-04T02:43:43-04:00
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~
#1174000 2026-10-04 19:55 UTCModified
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2026-10-04T02:43:43-04:00->2026-10-04T14:43:14-04:00
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