ML Engineer, Marketplace Research & Simulation

Whatnot Inc.; Northern, New York (KY, NY); Hybrid; USD 210,000 - 300,000; Full time

Benefits offered by this job

Flexible Time off Policy

Health Insurance options

Work From Home Support

Home office setup allowance

Monthly cell phone/internet allowance

Wellness monthly allowance

Childcare allowance

Lifetime family planning benefit

401k with employer match (US)

Job summary

Whatnot Inc. is seeking an experienced Machine Learning Engineer to lead research on marketplace dynamics, including simulation, auction mechanics, and long-term objective modeling.

You will transform hypotheses into production, build simulators, and develop models predicting ranking and policy effects for a multi-sided live marketplace. You will work with remote teams, contribute to publications and open-source projects, and influence cross-functional roadmaps while advancing experimental

Qualifications

• 5+ years of industry experience building and deploying ML models at scale.
• Depth in at least one area: recommendation systems, causal inference, off-policy evaluation, RL and bandits, auction/mechanism design, or marketplace experimentation.
• Track record applying scientific methods to real-world consumer data.
• Advanced proficiency in Python, SQL, and ML frameworks (PyTorch, XGBoost, etc).
• Strong grounding in applied statistics, experiment design and theoretical ML.
• Strong communication and leadership skills, ability to influence roadmaps across remote teams.

Responsibilities

• Lead research projects across marketplace dynamics: simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, or marketplace experimentation methods.
• Take ideas from hypothesis to production: literature review, prototyping, offline validation, shadow testing, and online experiments with partner teams.
• Build models of marketplace behavior: learned simulators predicting segment-level effects of ranking and policy changes.
• Model Whatnot's market mechanics: auction/bidding dynamics and discovery exposure as a portfolio problem.
• Advance evaluation techniques: off-policy evaluation, switchback/interference-robust designs, variance reduction.
• Contribute to Whatnot's external technical presence via publications and open-source work.

Skills

5+ years experience

ML model deployment

Python

SQL

Statistical methods

Communication

Leadership

Tools

PyTorch

XGBoost

Job description

Whatnot Inc. is seeking an experienced Machine Learning Engineer to lead research on marketplace dynamics, including simulation, auction mechanics, and long-term objective modeling.

You will transform hypotheses into production, build simulators, and develop models predicting ranking and policy effects for a multi-sided live marketplace. You will work with remote teams, contribute to publications and open-source projects, and influence cross-functional roadmaps while advancing experimental