Senior Machine Learning Engineer, Ads

About the role

We are seeking experienced machine learning engineers who thrive on solving complex challenges and designing scalable, ground-breaking solutions. In this role, you will develop deep learning-based models for performance advertising business. Your work will lay the foundation to deliver effective performance ads to our users and more business value to our advertisers. You will build innovative machine-learning solutions to power ad ranking algorithms and personalized advertising experiences. With our ads system still in its early stages, this is a unique opportunity to shape and develop a world-class, ML-driven advertising platform from the ground up.

Responsibilities

• Drive the design and implementation of machine learning solutions for ad ranking algorithms.
• Design and implement large-scale recommendation models.
• Author specs for new features and improvements.
• Collaborate with other teams within Roblox to ensure a community-first approach in product development.
• Balance researching new technologies with a practical approach to integrate research efforts into Roblox products.
• Communicate with the industry and communities where applicable and act as an ambassador for Roblox.

Requirements

• 5+ years of experience designing and building scalable machine learning solutions to solve real-world production use cases.
• Experience with transformer-based model training, inference, and product integration is a plus.
• BS in Computer Science or a related discipline; advanced degrees are a plus.
• Initiated and facilitated challenging technical decisions across multiple teams and organizations.
• Deeply technical but always start with the needs of the user, whether they are Roblox users or internal engineers.
• Creative and strategic approach to solving hard problems; ability to simplify the complex and bring in fresh ideas.

Pay

For roles based at our headquarters in San Mateo, CA, the starting base pay range is $259,030—$311,430 USD. The actual base pay is dependent upon professional background, training, work experience, location, business needs, and market demand.

Schedule

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

Benefits

All full-time employees are eligible for equity compensation and benefits.