OpportunityOfferwall by Unity is a leading mobile advertising and monetization platform that empowers game developers to maximize revenue and engage users through rewarded experiences. For over a decade, we've connected millions of players with offers that provide tangible in-app value, and we're now building the next generation of that product.
Rewarded advertising attracts fraud. Every conversion attempt on Offerwall and the Unity Rewards app is scored in real time by our fraud detection stack: a prediction service, an online feature store, streaming and batch feature pipelines, and a rules engine that decides what gets paid out. When fraud gets through, money leaks from our advertisers and our business.
We're seeking a Machine Learning Engineer to own the ML side of Offerwall fraud prevention. You'll take our real-time anomaly detection and device risk models from development into production, build the labeled fraud dataset and evaluation methodology the team measures itself against, and modernize how we train, serve, and monitor models. You'll work closely with data engineering, backend, and product partners who own the systems your models plug into.
This is a hands-on role with real scope. You'll be one of a small group of engineers responsible for fraud ML end to end, and you'll have a direct line from the models you ship to dollars saved.
What you'll be doing- Ship Fraud Models to Production: Take our real-time anomaly detection and device risk models from development to production, so their output drives payout and blocking decisions.
- Build the Ground Truth: Create and maintain a golden labeled fraud dataset, and define the evaluation methodology and baseline fraud-efficacy metrics the team uses to judge every model and rule change.
- Own Features End to End: Design and evolve the streaming and batch features that feed our Redis online feature store, partnering with data engineering on freshness, correctness, and lineage.
- Modernize ML Infrastructure: Plan and drive the evolution of our training and serving stack, including evaluating a move from SageMaker to Kubeflow and KServe, with attention to latency on the real-time scoring path.
- Detect New Fraud Patterns: Investigate fraud spikes, analyze user and device behavior, and turn findings into new detection signals, features, and models.
- Operate & Document: Monitor model and feature health in production, write runbooks and data lineage docs, and participate in on-call for the fraud detection stack.
What we're looking for- Production ML Experience: Several years building ML models and taking them all the way to production, including deployment, monitoring, and iteration after launch.
- Fraud, Risk, or Anomaly Detection: Hands-on experience with fraud detection, abuse prevention, risk scoring, or anomaly detection, including working with sparse, noisy, or adversarial labels.
- Real-time Serving & Feature Engineering: Experience with low-latency model serving and online/offline feature pipelines (for example Redis or another online feature store, Kafka or similar streaming, Airflow).
- Evaluation Rigor: Ability to build labeled datasets from imperfect signals and design evaluation methods that hold up when fraud patterns shift.
- Core Technologies: Strong Python and SQL. Working knowledge of a cloud ML platform such as AWS SageMaker, Kubeflow, or KServe.
- Ownership & Collaboration: You take ambiguous problems to shipped outcomes with limited oversight, write things down, and work well with backend, data, and product partners. You use AI coding tools to move faster.
You might also have- Experience with ad fraud, install/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 device and user linking.
- Experience migrating ML serving between platforms, or building MLOps tooling on Kubernetes.
- Background in mobile ad tech, mobile games, or app monetization.
Additional DetailsBase Salary Range: We determine the base salary range for this role based on your primary work location:
Zone A: $178,700 - $232,300
Zone B: $159,100 - $206,800
Zone C: $140,700 - $182,900
This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.
BenefitsAt Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.
Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.
While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program
