🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
Minimum qualifications: Bachelor's degree or equivalent practical experience. 2 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data. 2 years of experience utilizing Python and SQL to solve engineering problems. Experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning). Preferred qualifications: Experience working with abuse, spam, fraud or malware. Experience working on product policy analysis and identifying policy risks. Experience working with CBRN and cyber threat risks in GenAI. Experience using statistical analysis and hypothesis testing. Experience analyzing ML models performance or working on LLMs. Strong influencing skills and ability to work in a dynamic environment. About The Job At Google we work hard to earn our users’ trust every day. Gaining and retaining this trust is critically important to Google’s success. We defend Google's integrity by fighting spam, fraud and abuse, and develop and communicate state-of-the-art product policies. The Trust and Safety team reduces risk and protects the experience of our users and business partners across Google's expanding base of products. We work with a variety of teams from engineering to legal and public policy to set policies and combat fraud and abuse in a scalable way, often with an eye to finding industry-wide solutions. Trust and Safety team members are motivated to find innovative solutions, and use technical know-how, user insights and proactive communication to pursue the highest possible quality and safety standards for users across Google products. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. Ireland: €90000 - €92000 (EUR) + 15% bonus target + equity + benefits Responsibilities Learn more about benefits at Google . Help to establish metrics to benchmark Generative-AI issues and quantify improvements. Develop datasets and run evals for engineers to evaluate and improve Search, Labs & Assistant products. Perform complex data analyses to derive insights that help identify and fight abuse across our products. Analyze and debug escalations and identify trends that can indicate bigger product risks. Use technical judgement to drive project delivery, challenge proposals and identify risks. Manage multiple interdependent projects of moderate to high complexity and scope against crashed timelines. Improve tools through data analysis, technical expertise, and presentations to key stakeholders. Enhance our operational workflows via process improvements and identification of automation opportunities. Review graphic, controversial, and sometimes offensive/sensitive content. Collaborate with other teams & functions: RAI, Policy, Product, etc. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.