Machine Learning Engineer, Applied Research

Whatnot
New York
Workplace: HybridFull timeUSD 210,000 - 300,000 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Communication","Leadership","Low ego","Growth mindset","High-impact drive"]

Lead applied research projects for a live marketplace, turning hypotheses into production-ready models and experiments. Own work across simulation, auction/allocation mechanics, exploration and information value, and off-policy evaluation with robust experiment designs. Build learned simulators and surrogate models to predict segment-level effects and long-term outcomes, and help teams ship improvements to marketplace dynamics. Publish and contribute to external technical work.

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Whatnot
Whatnot
1 day ago

Machine Learning Engineer, Applied Research

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Source: Company careers pageValidated by: Fursa AI
Last checked: 15 hours agoStatus: Live

Job Summary

Lead applied research projects for a live marketplace, turning hypotheses into production-ready models and experiments. Own work across simulation, auction/allocation mechanics, exploration and information value, and off-policy evaluation with robust experiment designs. Build learned simulators and surrogate models to predict segment-level effects and long-term outcomes, and help teams ship improvements to marketplace dynamics. Publish and contribute to external technical work.
Location: New York
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Lead marketplace dynamics research across areas including simulation, auction/allocation mechanics, long-term objective modeling, exploration/information value, and experimentation methods.
  • •Take ideas from hypothesis to production using literature review, prototyping, offline validation, shadow testing, and online experiments with partner teams.
  • •Build learned simulators and surrogate models to predict segment-level effects and long-term marketplace outcomes.
  • •Advance evaluation of changes in a multi-sided marketplace using off-policy evaluation and robust experiment designs.
  • •Contribute to external technical presence via publications, open-source work, and public benchmarks.

Pay and Benefits

Salary: USD 210,000 - 300,000 annually
Perks:Health InsuranceDentalVisionRetirement401kPensionPaid LeaveParental LeaveHome Office

Key Requirements

  • •5+ years of industry experience building and deploying ML models to solve user problems at scale.
  • •Depth in at least one area such as recommendation systems, causal inference, off-policy evaluation, reinforcement learning/bandits, auction/mechanism design, or marketplace experimentation.
  • •A track record of applying scientific methods to real-world problems using consumer-scale data.
  • •Advanced proficiency in Python, SQL, and common ML frameworks like PyTorch and XGBoost.
  • •Strong grounding in applied statistics, experiment design, and theoretical machine learning.
Experience:5+ years
Skills:CommunicationLeadershipLow egoGrowth mindsetHigh-impact drive
Tech Stack:PythonSQLPyTorchXGBoost

Company Brief

Whatnot
Whatnot is a live-stream shopping marketplace connecting sellers and collectors for trading cards, toys, and collectibles. The platform hosts live auctions and interactive streams, enabling creators and small businesses to sell directly to engaged communities.
Industry: Online Marketplaces
Company Size: Large (251 to 1,000 employees)
Growth: Scaleup
Valuation: Unicorn (USD 1B+)
Funding: Series D
Headquarters: United States
Founded: 2019
WebsiteLinkedIn