Senior Machine Learning Engineer, Ads

Unity Technologies SF•Mountain View, CA

15h

About The Position

Opportunity Offerwall by Unity is a mobile advertising and monetization platform serving game developers through rewarded experiences. Unity is hiring a Senior Machine Learning Engineer to own the machine-learning side of Offerwall fraud prevention. The role focuses on bringing real-time anomaly detection and device-risk models into production and ensuring their scores inform payout and blocking decisions. The engineer will build a labeled fraud dataset and evaluation methodology, develop and maintain model features, and modernize the systems used to train, serve, and monitor models. They will collaborate with data engineering, backend, and product partners, and will be part of a small team responsible for fraud machine learning end to end. The position also involves investigating fraud patterns, monitoring model and feature health, documenting systems and data lineage, and participating in on-call for the fraud detection stack. The role may be eligible for equity awards and participation in company incentive plans, in addition to base salary. Salary ranges vary by work location: Zone A $178,700–$232,300; Zone B $159,100–$206,800; Zone C $140,700–$182,900.

Requirements

Several years of experience building machine-learning models and taking them through production deployment, monitoring, and post-launch iteration.
Hands-on experience with fraud detection, abuse prevention, risk scoring, or anomaly detection, including sparse, noisy, or adversarial labels.
Experience with low-latency model serving and online/offline feature pipelines, such as Redis or another online feature store, Kafka or similar streaming technology, and Airflow.
Ability to build labeled datasets from imperfect signals and design evaluation methods that remain useful as fraud patterns shift.
Strong Python and SQL skills.
Working knowledge of a cloud ML platform such as AWS SageMaker, Kubeflow, or KServe.
Ability to take ambiguous problems to shipped outcomes with limited oversight, document work, and collaborate with backend, data, and product partners.
Use of AI coding tools to work more efficiently.
Sufficient English knowledge for frequent professional verbal and written communication with colleagues and partners worldwide.

Nice To Haves

Experience with ad fraud, install or attribution fraud, or fraud in rewarded or incentivized advertising.
Experience with unsupervised or semi-supervised detection methods such as autoencoders, isolation forests, or graph-based approaches to linking devices and users.
Experience migrating ML serving between platforms or building MLOps tooling on Kubernetes.
Background in mobile ad tech, mobile games, or app monetization.

Responsibilities

Take real-time anomaly detection and device-risk models from development into production so their outputs inform payout and blocking decisions.
Create and maintain a golden labeled fraud dataset and define evaluation methods and baseline fraud-efficacy metrics for assessing model and rule changes.
Design and evolve streaming and batch features that feed the Redis online feature store, partnering with data engineering on freshness, correctness, and lineage.
Plan and drive improvements to the training and serving stack, including evaluating a possible move from SageMaker to Kubeflow and KServe while considering real-time scoring latency.
Investigate fraud spikes and user and device behavior, translating findings into detection signals, features, and models.
Monitor model and feature health in production.
Write runbooks and data-lineage documentation.
Participate in on-call for the fraud detection stack.
Collaborate with backend, data, and product partners.

Benefits

Comprehensive health, life, and disability insurance.
Commute subsidy.
Employee stock ownership.
Competitive retirement or pension plans.
Generous vacation and personal days.
Leave and family-care programs supporting new parents.
Office food and snacks.
Mental health and wellbeing programs and support.
Employee Resource Groups.
Global Employee Assistance Program.
Training and development programs.
Volunteering and donation matching program.
Potential eligibility for equity awards and company incentive plans, such as annual discretionary bonuses or sales commissions.