Six Figure Work

Principal/Senior Machine Learning Scientist - Search and Discovery

Roblox

Company websiteroblox.com (Roblox, opens in new tab)

Base salary $278,530  to $345,040

Employer-published annual base salary, USD. Advertised base range in San Mateo, CA

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  • LocationSan Mateo, CA
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (3 min ago) · observed since

About this job

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.

With Roblox’s daily active users growing at a record pace, we are seeking experienced machine learning researchers who thrive on solving complex challenges and designing scalable, ground breaking solutions. In this role, you will innovate on LLMs, VLMs, autoregressive models, or other large models for user understanding, content understanding, recommendation, and agentic search. Your work will lay the foundation for personalizing user experiences, enhancing engagement and retention, and driving growth within the creator ecosystem.

In search and discovery, you will contribute to the core systems that enable users to discover and interact with experiences across Roblox. On Search, that work spans the end-to-end user search journey, covering query suggestions, autocomplete, and retrieval and ranking. These systems drive exploration and engagement across all surfaces, helping users find relevant and exciting content. Looking ahead, our team aims to innovate further by developing auto-generated summaries, images, and videos from experience content to improve discoverability and inspire user exploration.

Our mission is to connect a billion users with the best content and connections at the right time, tackling diverse challenges in advertising, search, and discovery at an unprecedented scale. Join us and play a pivotal role in shaping the future of Roblox’s search and discovery.

You Will:

  • Design and implement the machine learning solutions that power agentic search and discovery systems to drive Roblox content distribution.
  • Design and implement large scale recommendation models.
  • In this role, you will innovate on LLMs, VLMs, autoregressive models, or other large models for query understanding, user understanding, content understanding, recommendation, and agentic search.
  • Design eval and post-training loops - SFT, preference optimization, and RL - for ranking, query understanding, and agentic systems.
  • Balance researching new technologies with a practical approach to integrate research efforts into the Roblox products.
  • Collaborate with other teams within Roblox to make sure we are building products with a community first approach.
  • Communicate with the industry and communities where applicable and be ambassador for Roblox.

You have:

  • You have 7+ (for principal) or 4+ (for senior) years of experience designing and building scalable machine learning solutions. Experienced with transformer based model training, inference, and product integration. Break down product requirements into iterative deliverable stages.
  • Depth in recommendation, search retrieval and ranking, or LLM post-training and agentic systems is a plus.
  • You have a BS, MS, or PhD in Computer Science or a related discipline or equivalent experience.
  • You have initiated and facilitated challenging technical decisions across multiple teams and organizations.
  • While deeply technical, you always start with the needs of the user, whether they are Roblox users or internal engineers.
  • A creative and strategic approach to solving hard problems. You simplify the complex. You bring in fresh ideas from new places.

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

$278,530—$345,040 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.

Source: Roblox on Greenhouse · View original posting (opens in new tab)

Pay in context

This role's base floor ($278,530) is above 89% of the 1,731 Data & ML roles in California listed on this site; 1 other lists the same floor. Their median floor is $184,000; the middle half runs from $154,300 to $224,000.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 8, 2026.

This range next to 6 other live Roblox roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Roblox roles with the nearest advertised base floor
RolePublished base
Principal/Senior Machine Learning Scientist - Search and Discovery (this listing)$278,530 - $345,040
Senior Product Manager, AI Compute Infrastructure$280,540 - $330,950
Senior Product Manager, App Performance & Architecture$280,540 - $330,950
Senior Product Manager, UGC Marketplace$280,540 - $330,950
Senior Product Manager, Engineering Acceleration$280,540 - $330,950
Senior/Principal Product Manager, Engine Networking$280,540 - $330,950
Principal Software Engineer, Agent Infrastructure$278,530 - $345,040

Same $100K to $400K scale as every card. All Roblox roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-02-26
Where this pay comes from

Location as the employer wrote it: San Mateo, CA, United States

$278,530—$345,040 USD

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.

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