Machine Learning Analyst, Egregious Harms, Trust and Safety
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Job Description
Machine Learning Analyst, Egregious Harms, Trust and Safety at Google
Trust & Safety team members are tasked with identifying and taking on the biggest problems that challenge the safety and integrity of our products. They use technical know-how, excellent problem-solving skills, user insights, and proactive communication to protect users and our partners from abuse across Google products like Search, Maps, Gmail, and Google Ads. On this team, you're a big-picture thinker and strategic team-player with a passion for doing what’s right. You work globally and cross-functionally with Google engineers and product managers to identify and fight abuse and fraud cases at Google speed - with urgency. And you take pride in knowing that every day you are working hard to promote trust in Google and ensuring the highest levels of user safety.
As an Engineering Analyst within the Trust and Safety team, you will be part of a global team that ensures the seamless detection and enforcement of some of the most egregious online harms (e.g., child sexual abuse materials and non-consensual intimate imagery). Through close partnerships with Product, Engineering, Policy, and Legal, you will leverage your technical acumen to design and develop novel solutions to further Google’s ability to fight this abuse worldwide.
At Google we work hard to earn our users’ trust every day. Trust & Safety is Google’s team of abuse fighting and user trust experts working daily to make the internet a safer place. We partner with teams across Google to deliver bold solutions in abuse areas such as malware, spam and account hijacking. A team of Analysts, Policy Specialists, Engineers, and Program Managers, we work to reduce risk and fight abuse across all of Google’s products, protecting our users, advertisers, and publishers across the globe in over 40 languages.
Minimum qualifications:
- Bachelor's degree or equivalent practical experience.
- 5 years of experience in data analysis, including identifying trends, generating summary statistics, and drawing insights from quantitative and qualitative data.
- Experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
Preferred qualifications:
- Master's degree in a quantitative discipline.
- Knowledge of current abuse techniques and practices.
- Ability to extract, manipulate, and apply machine learning techniques to high volumes of critical, product-related data.
- Ability in working with a variety of engineering stakeholders to gather requirements, explain models, and iterate to make improvements.
- Excellent written and verbal communication with the ability to describe technical implementations or analyses to a non-technical audience in an effective manner.
- Excellent problem-solving and critical thinking skills with attention to detail in an ever-changing environment.
Responsibilities:
- Develop scalable safety solutions for AI products across Google by leveraging advanced machine learning and AI techniques.
- Apply statistical and data science methods to thoroughly examine Google's protection measures, uncover potential shortcomings, and develop actionable insights for continuous security enhancement.
- Compute statistics (e.g., precision, recall) about the performance of complex technical models (Machine Learning systems, classifiers, Large Language Models) and recognize nuanced, easily missed problems in the performance of these systems.
- Lead multiple interdependent projects of moderate to high complexity and scope.
- Work cross-functionally to ensure coordination and alignment on objectives and key results.
- Review or be exposed to sensitive or graphic content as part of core role.
The US base salary range for this full-time position is $147,000-$216,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
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.
Key skills/competency
- Machine Learning
- Data Analysis
- Statistical Modeling
- AI Techniques
- ML Infrastructure
- Abuse Detection
- Problem Solving
- Cross-functional Collaboration
- Data Science
- Product Safety
How to Get Hired at Google
- Research Google's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Highlight relevant machine learning, data analysis, and Trust & Safety experience for Google.
- Showcase problem-solving: Prepare specific examples demonstrating your critical thinking and analytical skills.
- Emphasize collaboration: Detail experiences working cross-functionally with engineering and product teams at Google.
- Quantify your impact: Provide metrics and results for your achievements in past data analysis and ML roles.
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