{"id":3300818,"url":"https://alion.io/job/pinterest-staff-machine-learning-engineer-2","title":"Staff Machine Learning Engineer","company":{"id":75,"name":"Pinterest","domain":"pinterest.com","url":"https://alion.io/company/pinterest","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":80,"open_postings":26,"ghost_share":0,"stale_share":0.808,"repost_share":0,"time_to_fill_p50_days":49,"computed_at":"2026-10-28T05:59:10Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States","Palo Alto, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":189308,"max":389753,"currency":"USD","period":"year","gross":null,"usd_annual":389753},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Recommender Systems","optional":false}],"status":"live","first_seen_at":"2026-10-26T19:44:30Z","employer_posted_date":"2026-10-26","last_verified_at":"2026-10-28T20:23:48Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About Pinterest:\nMillions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\nDiscover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It’s Possible.\nAt Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\nThrough our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.\nGrowth Content Science builds the ML that decides which content we bring to people on our growth surfaces, with a focus on notifications. We own the real-time production stack behind that decision: candidate retrieval, L1 and L2 ranking, utility and blending, content quality along with copy generation and ranking. As a Staff Machine Learning Engineer, you'll personally build the most complex models and systems on this stack, hold the bar for code quality and healthy ML infrastructure and lead the technical direction for notification content ranking.\nWhat you'll do\nLead multiple technical sub-areas within Growth content science effectively.\nDrive Growth ML model improvements through AB test driven innovation loop - from ideation to production launches.\nOwn the health of our ML ecosystem: training pipelines, feature and serving infrastructure, evaluation frameworks and monitoring, AB test set up, etc.\nHelp raise the technical excellence bar through mentorship, reviews, evaluations, documentation, standard setting, etc.\nCollaborate and build strong working relationships with colleagues and stakeholders to tackle big, cross-functional, initiatives.\nWork closely with other engineering leaders to form technical directions and roadmaps.\nOperate autonomously, take ownership in complex and evolving environments and drive work effectively.\nIdentify and apply relevant state-of-the-art techniques from recent research and/or collaborate on novel research directions.\nContinuously optimize various parts of work by building and using cutting-edge AI tools.\nWhat we're looking for\nGraduate degree in Computer Science or in a related field\nMinimum of 8 years of experience in machine learning engineering, including hands-on experience building and shipping models for a large-scale, real-time, end-user production recommender system\nExpertise in recommender modeling, including sequence modeling of user behavior with transformer architectures, DNN rankers and generative and LLM-native recommenders\nExperience in building and operating high-QPS, latency-constrained ML systems, including training and serving infrastructure, and in owning the cost, latency and reliability tradeoffs\nExperience in industry-grade software engineering that others use as the example, and in conducting thorough code and design reviews that raise the quality of a team's work\nUnderstanding of content personalization and content quality as one problem, and of why cold-start and low-signal users break standard rankers\nExperience in leading technical work across teams, making timely decisions on hard tradeoffs and saying no when the user experience or the system health is at stake\nExperience in mentoring junior engineers\nOutstanding written and verbal communication skills, especially in a cross-functional set up\nDemonstrated experience using AI to improve speed and quality in applied research\nStrong track record of publications and patents\nIn-Office Requirement Statement:\nWe recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.\nThis role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.\nRelocation Statement:\nThis position is not eligible for relocation assistance. Visit ourPinFlex page to learn more about our working model.\nAt Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.\nInformation regarding the culture at Pinterest and benefits available for this position can be found here.\nUS based applicants only\n$189,308—$389,753 USD\nOur Commitment to Inclusion:\nPinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.\nBy submitting this application, I certify that all information submitted in my application and throughout the hiring process is true, accurate, and complete to the best of my knowledge. 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