Senior ML Scientist — Personalization & Monetization

102 Yahoo Inc.; United States; Hybrid; USD 128,000 - 267,000; Full time

Benefits offered by this job

Hybrid work options

Healthcare benefits

401k

Education stipends

Job summary

Yahoo Inc. in the United States seeks a senior ML leader to design and scale ranking, personalization and monetization models for Yahoo Mail. You will guide transformer-based and deep learning projects, mentoring researchers and engineers to deliver measurable business impact.

The role emphasizes collaboration with cross-functional squads, strong communication, and governance of model outputs across large-scale systems with a flexible hybrid work setup.

Qualifications

• PhD (preferred) or Master’s in CS, Statistics, Applied Math, or related field.
• 8+ years in machine learning/deep learning with scaling ranking or monetization systems.
• Proven ability to optimize business metrics and model governance.
• Strong Python and ML framework expertise; clear communication with engineers and leaders.

Responsibilities

• Lead design and strategy for ranking, personalization, and monetization models.
• Mentor researchers and engineers; translate research into production-ready systems.
• Collaborate with cross-functional teams to drive measurable business impact.
• Oversee adoption of transformers and large-scale DL methods with governance.

Skills

Machine learning fundamentals

Deep learning

Transformer models

Python

Communication

Leadership

Education

PhD preferred

Master's in CS/Statistics/Applied Math

Tools

TensorFlow

PyTorch

Hugging Face

Pandas

NumPy

Job description

Yahoo Inc. in the United States seeks a senior ML leader to design and scale ranking, personalization and monetization models for Yahoo Mail. You will guide transformer-based and deep learning projects, mentoring researchers and engineers to deliver measurable business impact.

The role emphasizes collaboration with cross-functional squads, strong communication, and governance of model outputs across large-scale systems with a flexible hybrid work setup.