Applied Scientist, Vector AI

Unity Technologies•Mountain View, CA

About The Position

Unity's Vector AI team sits at the intersection of large-scale machine learning and real-world impact: our models govern ad ranking and bidding decisions across billions of daily impressions. Get the models right so players can discover games they love. We're looking for an Applied Scientist with experience on user understanding, sequence modeling, and/or conversion prediction. What you'll be doing: Design and ship user behavior models that directly influence ad ranking, bidding, and conversion outcomes across billions of impressions. Own model quality from deployment onward: calibration, drift detection, and feedback loop management. Shape how the team builds, contributing to long-term technical strategy and overseeing engineering execution. Bridge the gap between ML complexity and business reality, communicating clearly with non-technical partners.

Requirements

Master or Ph.D. in Computer Science, Machine Learning, Statistics, related fields, or equivalent practical experience.
2+ years of hands-on experience designing, building, and operating ML systems at scale in ads, search, recommendations, or related domains.
Deep familiarity with at least one of: CVR/CTR prediction, auction theory, user modeling, or sequential recommendation.
Production experience in Python and at least one systems language (Go, Scala, C++, or similar).
Significant experience in one or more general-purpose programming languages like Python, Go, Scala, C++ or similar.
Knowledge of metric design, experimentation methodologies, and large-scale data.
Experience embracing AI as a strategic advantage in engineering, following established best practices for code quality and security.
Sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.

Nice To Haves

Experience with real-time bidding systems, auction dynamics, or marketplace optimization.
Publications or patents in relevant areas.

Responsibilities

Design and ship user behavior models that directly influence ad ranking, bidding, and conversion outcomes across billions of impressions.
Own model quality from deployment onward: calibration, drift detection, and feedback loop management.
Shape how the team builds, contributing to long-term technical strategy and overseeing engineering execution.
Bridge the gap between ML complexity and business reality, communicating clearly with non-technical partners.