This is not an ML-specialist role, but familiarity with ML for Ads integrity is always welcome. You’ll work closely with ML engineers and researchers and build systems that consume and operationalize ML-based signals, but your primary focus will be designing and operating robust backend and distributed systems. You’ll help determine how signals, rules, models, and human review come together into reliable integrity protections for advertisements that can operate at OpenAI scale.
This role is particularly well suited to an engineer who has built large-scale systems in integrity, trust and safety, anti-abuse, fraud, risk, security, or a related adversarial domain.
You will have significant ownership over what we build and how we build it, partnering across Integrity and Ads to establish the architecture and technical foundations that will protect OpenAI’s ads ecosystem as it grows.
This role is based in San Francisco. We offer relocation assistance to new employees.
In this role, you will
Design and build large-scale backend systems that detect and prevent harmful, deceptive, fraudulent, or policy-violating activity across the ads ecosystem.
Build low-latency integrity infrastructure capable of evaluating risk signals and making decisions in or near real time.
Develop scalable risk-signal pipelines, decision systems, rules and enforcement infrastructure across the advertiser and ads lifecycle.
Build advertiser onboarding, business verification, account-risk, fraud-detection, and abuse-prevention capabilities that make it harder for malicious actors to enter or exploit the ecosystem.
Develop systems that support ads-specific content safety and enable the detection and enforcement of unsafe, misleading, deceptive, or policy-violating ads.
Build protections against spam, fraudulent interactions, manipulation, and other adversarial behaviors that threaten the health of the ads ecosystem.
Partner with ML teams to integrate classifiers and model-based signals into production integrity systems, including both lightweight real-time protections and more sophisticated asynchronous detection.
Build feedback loops, review systems, and integrity metrics that improve detection quality while carefully managing false positives and impact on legitimate advertisers and users.
Create tooling and infrastructure that enable operations and policy teams to investigate abuse and make fast, consistent, and explainable decisions.
Engineer systems that adapt as adversaries change their tactics and support effective experimentation, monitoring, and incident response.
Partner closely with Ads Engineering to integrate integrity protections throughout the ads platform without compromising reliability, latency, or product quality.
Help define the technical strategy and architecture for Ads Integrity as both the product and underlying threat landscape evolve.
You might thrive in this role if you
Have significant experience building and operating large-scale backend or distributed systems.
Have worked on integrity, trust and safety, anti-abuse, fraud, risk, security, business verification, or another domain where systems must operate against sophisticated or evolving adversaries.
Have built detection, decisioning, enforcement, verification, investigation, or risk infrastructure in production.
Understand how rules, heuristics, risk signals, ML-based signals, and human review can work together within a dependable production system.
Are comfortable building ML-adjacent infrastructure and partnering closely with ML teams without needing to be an ML domain expert.
Have built low-latency, high-throughput services or data pipelines with demanding reliability, correctness, privacy, and security requirements.
Can reason about false positives, adversarial behavior, explainability, auditability, and the operational impact of automated enforcement.
Think holistically about threat models, system architecture, data quality, observability, user impact, and ecosystem health.
Can define technical direction in an ambiguous 0→1 environment and independently drive complex work across teams.
Communicate clearly and work effectively across engineering, product, policy, safety, security, operations, and machine-learning teams.
Have experience with ads, ads integrity, advertiser systems, or ads fraud. This is a plus, but not a requirement.
Are excited to build the integrity foundation for a new product area rather than inherit a mature system.
About OpenAI
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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