{"id":3801836,"url":"https://alion.io/job/google-senior-software-engineer-machine-learning-discover-interest-modeling","title":"Senior Software Engineer, Machine Learning, Discover Interest Modeling","company":{"id":82,"name":"Google","domain":"google.com","url":"https://alion.io/company/google","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Career site","truth_index":{"grade":"B","score":78,"open_postings":134,"ghost_share":0.045,"stale_share":0.739,"repost_share":0.045,"time_to_fill_p50_days":30,"computed_at":"2026-11-08T05:47:12Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Recommender Systems","optional":false},{"name":"TensorFlow","optional":false},{"name":"Transformers","optional":false}],"status":"live","first_seen_at":"2026-11-05T10:37:46Z","employer_posted_date":"2026-11-05","last_verified_at":"2026-11-08T07:08:53Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"About the job\nGoogle's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.\nDiscover is Google's personalized interest feed. With daily active users, it is one of the largest feed recommendation products in the world.\nIn this role, the profile captures each person's long-term interests, favorite creators and in-the-moment intent. As these models drive recommendations a day, among the most important personalization signals in downstream ranking, and feed personalization across Google.\nEvery Discover feed starts with us, from a constantly refreshing corpus of articles, videos, creator posts and AI-generated content, our retrieval and pre-ranking stack selects the applicants most relevant to each person.\nIn Google Search, we're reimagining what it means to search for information - any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally. \nIndividual pay is determined by factors including job-related skills, experience, and relevant education or training.US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits\nLearn more about benefits at Google.\nResponsibilities\nAdd predictive modeling of the interests and creators a user will engage with next. Train with multi-objective goals (engagement, satisfaction).\nRedesign the interest vocabulary for much higher precision, and evaluate learned alternatives to today's interest vocab.\nBuild deep, sequence-based token models that learn from long user activity histories across Google products.\nBuild offline evaluation that predicts online results (profile-quality autoraters, retrieval and ranking metrics), and run well-sliced live experiments.\nDesign a shared token description, feature set, and training objectives across token types.\nQualifications\nMinimum qualifications:\nBachelor’s degree or equivalent practical experience.\n5 years of experience with machine learning algorithms and tools (e.g., TensorFlow), Recommender Systems, deep learning, or personalization.\n3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.\n3 years of experience building and deploying recommendation systems models 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