ML Discovery Engineer: Personalization & Feeds

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

Benefits offered by this job

Health Insurance options

Work From Home Support

Home office setup allowance

Cell phone & internet allowance

Parental Leave

401k with employer match

Job summary

Whatnot is seeking a Machine Learning Scientist to design, develop, and productionize ML models powering personalized buyer experiences and feed recommendations. You will own end-to-end ML projects from scoping to online experimentation, coordinating with Backend Engineers to ship production-grade solutions.

The role requires 4+ years of experience with consumer-scale data, strong Python/SQL, and ML frameworks such as PyTorch and XGBoost, plus leadership and communication skills in a remote

Qualifications

• 4+ years of industry experience building and deploying ML models at scale.
• Experience applying scientific methods to real-world problems on consumer data.
• Advanced proficiency in Python, SQL and ML frameworks (PyTorch, XGBoost).
• Strong communication and leadership skills; ability to influence roadmap in a remote environment.
• Proficiency in applied statistics and data visualization tools.

Responsibilities

• Lead the design, development, and productionization of ML models powering feed recommendations and buyer personalization.
• Lead ML projects end-to-end: scoping, data collection, feature engineering, training, deployment, and online experimentation.
• Support product initiatives like exploration, international, new buyer/seller and small category growth.
• Collaborate with Backend Engineers to productionize ML solutions and support feed systems.
• Drive ML best practices, grow team ML knowledge, and scale production models.

Skills

Leadership

Communication

Statistics

Experimentation

Remote collaboration

Tools

Python

SQL

PyTorch

XGBoost

Job description

Whatnot is seeking a Machine Learning Scientist to design, develop, and productionize ML models powering personalized buyer experiences and feed recommendations. You will own end-to-end ML projects from scoping to online experimentation, coordinating with Backend Engineers to ship production-grade solutions.

The role requires 4+ years of experience with consumer-scale data, strong Python/SQL, and ML frameworks such as PyTorch and XGBoost, plus leadership and communication skills in a remote