Applied ML Scientist II — Personalization & GenAI

The Washington Post; Washington (District of Columbia); On-site; USD 109,000 - 181,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

401(k) match

Paid time off

Parental leave

Mental health resources

Pet insurance

Job summary

The Washington Post is seeking an Applied Machine Learning Scientist 2 to build AI/ML systems for reader personalization, recommendations, and discovery. You will collaborate with scientists, engineers, data teams, product managers, editors, and other stakeholders to turn large-scale data into intelligent reader experiences.

You will work on personalization, ranking, user modeling, and content discovery, applying embeddings, transformers, two-tower architectures, and learning-to-rank techniques.

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Statistics, Machine Learning, or a related field.
• 2+ years of applied ML, data science, or recommender systems experience.
• Experience with Python and at least one ML framework (PyTorch, TensorFlow, or JAX).

Responsibilities

• Design, train, evaluate, and deploy ML models for personalization, recommendation, ranking, user modeling, and content discovery.
• Build and improve systems for For You, homepage ranking, article recommendations, related content, and real-time user modeling.
• Apply modern ML techniques including embeddings, transformer-based models, two-tower architectures, learning-to-rank, and GenAI-based approaches.
• Support AI-powered reader experiences such as content understanding, question answering, and personalized content recommendations.
• Collaborate with cross-functional teams and design offline/online evaluations, including A/B tests and causal analysis.

Skills

Python

PyTorch

TensorFlow

JAX

Recommender systems

NLP

GenAI

Experimentation

Education

Bachelor's degree in CS/Math/Stats/ML

Tools

AWS

GCP

Spark

Beam

BigQuery

Job description

The Washington Post is seeking an Applied Machine Learning Scientist 2 to build AI/ML systems for reader personalization, recommendations, and discovery. You will collaborate with scientists, engineers, data teams, product managers, editors, and other stakeholders to turn large-scale data into intelligent reader experiences.

You will work on personalization, ranking, user modeling, and content discovery, applying embeddings, transformers, two-tower architectures, and learning-to-rank techniques.