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Staff Research Scientist - Algo Brain

🕒 8 days ago
Machine LearningDeep LearningModel Architecture DesignTensorflow
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📜 Description

  • Identify opportunities to improve production CTR, CVR, and value prediction models.
  • Design and implement deep learning architectures, adapting research ideas or developing new approaches.
  • Bring validated model improvements into production with model-owning teams and verify offline gains hold in production.
  • Standardize model evaluation, comparison, and optimization methods, and build tools to accelerate model development.
  • At Staff level, set technical direction, lead architecture changes across models and teams, and mentor colleagues.

🛠️ Requirements

  • Experience with large-scale recommendation, ads ranking or CTR/CVR prediction models.
  • Experience with multi-task, multi-domain or user-sequence models.
  • Experience defining ML experimentation and optimization methodology: how model variants are evaluated, compared, tuned and diagnosed.

✨ Benefits

  • Comprehensive benefits
  • Fully stocked kitchen
  • Location-specific perks
  • Hybrid work model with 3 days in-office and the option to come in more often
Full job description

Realize your potential by joining the leading performance-driven advertising company!

As a Staff Research Scientist on Brain, a global R&D team in Taboola's Algorithms Craft Center, you'll play a vital role in advancing the deep learning models behind Taboola's recommendations and ads. This role is based in our Taipei office. It is a chance to do research that ships: you'll bring new ideas from deep learning and recommender systems research into models that run at Taboola's scale, rethink how they are built, and see your work directly improve a live production system. You'll also help shape the methodology algorithm engineers across the company use to develop and improve models.

In this role, you own model improvements end to end, from finding the opportunity to seeing the gain in production. Beyond your own projects, you set technical direction for a problem area, lead architecture changes across models and teams, and help the people around you grow through design reviews and mentoring.

To thrive in this role, you'll need:

  • Deep expertise in machine learning and deep learning, built on large-scale problems in any domain: recommendation, ads, search, NLP, vision, speech.
  • A track record of designing model architectures for a specific problem, not only applying existing ones, and building them yourself: you implement and train your models in any framework (TensorFlow, PyTorch or others).
  • Research judgment: you turn an open modeling problem into clear hypotheses and design rigorous studies that prove or rule them out.
  • Proven depth, shown by at least one of: measurable improvements to machine learning models in production; papers at top venues such as KDD, RecSys, WWW, NeurIPS or ICML, or venues of similar standing; top ranks in machine learning competitions such as Kaggle, KDD Cup or RecSys Challenge.
  • MSc or PhD in Computer Science, Mathematics, Statistics, Engineering or a related field, or equivalent research experience and expertise.
  • Clear written and spoken English, for working with teams across time zones.

Bonus points if you have:

  • Experience with large-scale recommendation, ads ranking or CTR/CVR prediction models.
  • Experience with multi-task, multi-domain or user-sequence models.
  • Experience defining ML experimentation and optimization methodology: how model variants are evaluated, compared, tuned and diagnosed.

How you'll make an impact:

  • Find where our production models for CTR, CVR and value prediction can improve fundamentally: architecture, representation, training objectives, training regime.
  • Propose new model architectures and methods, adapting ideas from research and industry and creating new ones when existing methods do not fit.
  • Design the studies that prove an idea works, and take proven improvements to production together with the teams that own each model.
  • Improve how models are developed across the company: define how models are evaluated, compared and optimized.

Our tech stack: TensorFlow, Spark and Airflow, on a heavily customized internal platform.

Why Taboola?

If you ask Taboolars what they love about working here, they’ll tell you they’ve been empowered to realize their full potential while growing and learning from smart, talented peers. 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, a fully stocked kitchen, and location-specific perks.

  • Flexibility: Hybrid work model with 3 days in-office and the option to come in more often if desired.

  • Work with the biggest names: We work with some of the biggest names in the business. Our publisher partners include Yahoo, Conde Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, Expedia and Honda.

Ready to realize your potential?

Taboola is an equal opportunity employer. We value diversity and are committed to fostering an inclusive environment. Employment is based on 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.

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