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Senior Algorithm Engineer, Recommendations

Taboolaתל אביב, ישראלהיברידידרגה: בכיר/ה

פורסם לפני 14 ימים · 0 מועמדים

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תובנת Willbi

התפקיד במילים פשוטות

בתפקיד זה תעסקו בתכנון, אימון ופריסה של מודלי למידה עמוקה עבור מערכות המלצת תוכן מורכבות ורחבות היקף. העבודה כוללת הובלת מחזור החיים המלא של המודלים, החל משלב המחקר והפרוטוטייפ ועד להטמעה בסביבות ייצור בעלות ביצועים גבוהים וזמני תגובה מהירים. כמו כן, תשתפו פעולה עם צוותי מוצר ופיתוח ותסייעו בחניכת מהנדסים צעירים יותר.

חובה
  • 4+ years of experience building deep learning and machine learning solutions end-to-end, from research and experimentation through production
  • MSc or PhD in Computer Science, Mathematics, Engineering, Statistics, or a related field
  • Strong foundations in machine learning, deep learning, and statistical modeling
  • Experience building large-scale deep learning recommendation systems, including areas such as retrieval, ranking, embeddings, or personalization
  • Strong software engineering skills in languages such as Python or Java, with experience developing production ML systems
יתרון
  • Experience with modern recommendation architectures such as two-tower models, sequence models, or transformers
  • Experience using AI coding tools (such as Claude Code or Cursor) to accelerate development, experimentation, and code quality

חולץ מתיאור המשרה · מתעדכן אוטומטית

למי זה מתאים

התפקיד מתאים לבעלי תואר שני או שלישי בתחומים כמותיים עם לפחות 4 שנות ניסיון בפיתוח פתרונות למידה עמוקה מקצה לקצה, ובפרט במערכות המלצה בקנה מידה גדול. הוא פחות יתאים למי שאין לו ניסיון מוכח בהעברת מודלים ממחקר לסביבת פרודקשן או למי שאינו שולט בפייתון או ג'אווה.

תיאור המשרה המלא

המשרה המקורית · נשמר לעיון

Realize your potential by joining the leading performance-driven advertising company! As a Senior Algorithm Engineer on the Algorithms team in our Tel Aviv office, you’ll play a vital role in building intelligent recommendation systems that shape how billions of users discover content across the open web. You’ll design and evolve large-scale deep learning models that power personalization, content recommendations, and user engagement. Working at the intersection of machine learning, data, and engineering, you’ll take models from research and experimentation through production, creating solutions that directly impact user experience, publisher revenue, and marketplace performance. To thrive in this role, you'll need: • 4+ years of experience building deep learning and machine learning solutions end-to-end, from research and experimentation through production. • MSc or PhD in Computer Science, Mathematics, Engineering, Statistics, or a related field, with strong foundations in machine learning, deep learning, and statistical modeling. • Experience building large-scale deep learning recommendation systems, including areas such as retrieval, ranking, embeddings, or personalization. • Strong software engineering skills in languages such as Python or Java, with experience developing production ML systems. • Proven ability to take models from prototype to scalable, high-performance production environments. Bonus points if you have: • Experience with modern recommendation architectures such as two-tower models, sequence models, or transformers. • Experience using AI coding tools (such as Claude Code or Cursor) to accelerate development, experimentation, and code quality. How you’ll make an impact: • Design, train, and deploy deep learning models for recommendation systems, including candidate generation, ranking, CTR/CVR prediction, and user intent modeling. • Own the full machine learning lifecycle, from research and prototyping through production deployment, A/B testing, monitoring, and optimization. • Build and evolve large-scale models that serve low-latency, high-throughput production traffic. • Analyze user behavior and engagement data to identify opportunities for algorithmic improvements. • Partner with Product, Engineering, and Business teams to translate product goals into scalable ML solutions with measurable impact. • Mentor junior engineers and contribute to technical design reviews, code reviews, and deep technical investigations. Why Taboola? If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about: Adam Singolda, Taboola Founder and CEO says: "You can copy anything from another business but you can’t copy a company’s culture." Well-being: Enjoy comprehensive benefits and well-being programs tailored to the region, a fully stocked kitchen, and location-specific perks. Flexibility: We offer a hybrid work schedule with 3 days in-office, with an option to come in more often if desired. Work with some of the biggest names: Our publisher partners include Yahoo, Condé Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia. Ready to realize your potential? Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need. Learn more about #TaboolaLife on LinkedIn , Facebook , Instagram , X , YouTube , & the Taboola Life Blog . About Taboola Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale. #LI-DN1 #LI-Hybrid

אודות Taboola
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פורסם לפני 14 ימים · 0 מועמדים
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