Senior Machine Learning Engineer, Ads
Company websiteunity.com (Unity, opens in new tab)
Base salary From $140,700
Employer-published annual base salary, USD. Advertised base range in United States
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationUnited States
- WorkplaceWorkplace not stated
- Status at last checkSource accepting applications when checked
- Last checked (1 h ago) · observed since
About this job
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.
Additional Details
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.
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
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. 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.
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.
Headhunters and recruitment agencies may not submit resumes/CVs through this Web site or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us. Please take a moment to review our Prospect and Applicant Privacy Policies. Should you have any concerns about your privacy, please contact us at [email protected].
Source: Unity on Workday · View original posting (opens in new tab)
Pay in context
This role's base floor ($140,700) is above 13% of the 1,503 Data & ML roles in California listed on this site; 1 other lists the same floor. Their median floor is $187,000; the middle half runs from $158,941 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.
This listingSenior Machine Learning Engineer, AdsFrom $140,700
Sr. Machine Learning EngineerFrom $140,700
Corporate Communications ManagerFrom $139,400
Senior Backend Engineer, Ads PrivacyFrom $135,800
Senior Machine Learning Engineer, Ads Modeling$148,700 to $244,600
Senior Machine Learning Engineer, Vector Bidding Science$148,700 to $244,600
Staff Software DeveloperFrom $157,800
Chart as a table
| Role | Published base |
|---|---|
| Senior Machine Learning Engineer, Ads (this listing) | From $140,700 |
| Sr. Machine Learning Engineer | From $140,700 |
| Corporate Communications Manager | From $139,400 |
| Senior Backend Engineer, Ads Privacy | From $135,800 |
| Senior Machine Learning Engineer, Ads Modeling | $148,700 - $244,600 |
| Senior Machine Learning Engineer, Vector Bidding Science | $148,700 - $244,600 |
| Staff Software Developer | From $157,800 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-11-03
Where this pay comes from
Location as the employer wrote it: US (regional bands)
Zone C: $140,700 - $182,900
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
