Senior/Principal Machine Learning Engineer, User Connections

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.

Check out the role overview below If you are confident you have got the right skills and experience, apply today.

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.

What You’ll Do :

We are looking for an accomplished Machine Learning engineer to build large-scale ML systems to connect people on Roblox.

You will build the next generation of social graph embeddings and systems to empower Roblox users to discover, search for, and connect with their real-life friends and interests on Roblox.

You will drive company-level objectives for friending growth and user retention.

You will :

• Apply ML on the Roblox social graph to power critical social features such as People You May Know, People Search, Friendship Score, etc.
• Build ML systems that scale to hundreds of millions of users and experiences.
• Define the long-term ML strategies across the team.
• Be a tech lead and mentor junior engineers.
• Collaborate with product and design to push the boundaries of what is possible.

You have :

• 8+ years of experience building and shipping ML models in large distributed systems, ideally in recommendation systems or search engines.
• Initiated and built complicated technical solutions. You have the technical expertise to influence product direction and you can foster a culture of technical excellence.
• Knowledge and experience with training embeddings and applying them in large distributed systems.
• Passion about working on large-scale and consumer-facing applications.
• Experience in applying ML in large-scale social networks is a plus.

Compensation and Benefits :

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.

Annual Salary Range : $283,780 $331,640 USD

Work Environment :

Roles that are based in our San Mateo, CA Headquarters are in-office Tuesday, Wednesday, and Thursday, with optional in-office on Monday and Friday (unless otherwise noted).

You’ll Love :

• Industry-leading compensation package
• Excellent medical, dental, and vision coverage
• A rewarding 401k program
• Flexible vacation policy (varies by exemption status)
• Roflex - Flexible and supportive work policy
• Roblox Admin badge for your avatar
• At Roblox HQ :
• Free catered lunches five times a week and several fully stocked kitchens with unlimited snacks
• Onsite fitness center and fitness program credit
• Annual CalTrain Go Pass

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 for all candidates during the interview process.

J-18808-Ljbffr