ML Engineer - Discovery & Personalization, Lead & Deploy

Whatnot; New York (NY); On-site; USD 180,000 - 245,000; Full time

Job summary

Whatnot is seeking a Machine Learning Scientist to lead the design, development, and productionization of ML models powering feed recommendations and buyer personalization. You will oversee end-to-end ML projects, from data collection and feature engineering to training, deployment, and online experimentation.

The role requires 4+ years of industry experience, strong Python/SQL skills, and proficiency with PyTorch or XGBoost.

Qualifications

• 4+ years of industry experience building and deploying ML models.
• Applied statistics with strong visualization capabilities.
• Advanced proficiency in Python and SQL; experience with ML frameworks like PyTorch and XGBoost.
• Strong communication and leadership skills; able to influence roadmap in a remote environment.
• Experience building ML applications for Discovery/Personalization and some backend development.

Responsibilities

• Lead the design, development, and productionization of ML models for feed recommendations and buyer personalization.
• Oversee ML-based projects from scoping through deployment and online experimentation.
• Collaborate with Backend Engineers to ship ML solutions into production.
• Drive ML best practices across Buyer and Discovery teams and scale production models.

Skills

ML model deployment

Python

SQL

Communication

Statistics

Tools

PyTorch

XGBoost

SQL

Job description

Whatnot is seeking a Machine Learning Scientist to lead the design, development, and productionization of ML models powering feed recommendations and buyer personalization. You will oversee end-to-end ML projects, from data collection and feature engineering to training, deployment, and online experimentation.

The role requires 4+ years of industry experience, strong Python/SQL skills, and proficiency with PyTorch or XGBoost.