Senior Machine Learning Engineer, Ads

Unity; Mountain View (CA); Presencial; USD 179.000 - 232.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Commute subsidy

Stock ownership

Retirement plan

Vacation days

Parent leave

Office snacks

Mental health support

Employee groups

Assistance program

Training programs

Volunteer match

Descripción de la vacante

Unity’s Offerwall fraud platform seeks a Machine Learning Engineer to own the ML end-to-end, transforming real-time anomaly detection and device risk models into production. You will build a golden fraud dataset, define evaluation metrics, and ensure models and rules align with payout and blocking decisions.

You will collaborate with data engineering, backend, and product partners; modernize training and serving, evaluate SageMaker to Kubeflow/KServe, and monitor health with runbooks and data

Formación

• Production ML experience in real-time systems.
• Experience with fraud detection or anomaly detection.
• Experience with low-latency model serving and feature pipelines.
• Ability to design evaluation methods for evolving fraud patterns.
• Strong Python and SQL; familiarity with AWS SageMaker, Kubeflow or KServe.
• Collaborative, able to work across backend, data, and product teams.

Responsabilidades

• Ship fraud models to production and influence payout decisions.
• Build and maintain a labeled fraud dataset and evaluation metrics.
• Design streaming and batch features feeding online feature store.
• Evolve training and serving stack; evaluate SageMaker to Kubeflow/KServe.
• Investigate fraud spikes and derive new detection signals.
• Monitor model health and participate in on-call/runbooks.

Conocimientos

Production ML

Fraud detection

Real-time serving

Evaluation methods

Python

SQL

CloudML: SageMaker

Herramientas

Redis

Kafka

Airflow

Kubeflow

KServe

SageMaker

Descripción del empleo

Opportunity

Offerwall 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.

Base 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.

Benefits

At 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.

• 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

Life at Unity

Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.

Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

This position requires the incumbent to have a 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.

If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.