Machine Learning Experimentation

Machine Learning Experimentation Data Jobs

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Today

Machine Learning Engineer, Applied Research

Whatnot New York, NY

New York, NY

Today

$207k - $290k/yr Full time Artificial Intelligence Data Science Engineer

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Job Description

Whatnot is hiring a Machine Learning Engineer, Applied Research for a hybrid role based in New York City (within commuting distance, up to 50 miles from the hub). You will lead applied research and machine learning work that turns marketplace questions into models and experiments, moving from hypothesis to production and helping improve how decisions and experimentation are evaluated.

What you’ll do

Lead applied research projects focused on marketplace dynamics, including simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, and marketplace experimentation methods.
Drive work from hypothesis to production through literature review, prototyping, offline validation, shadow testing, and shipping online experiments through partner teams in Discovery and Seller.
Build system-level models of how the marketplace behaves, such as learned simulators that estimate segment-level impacts from ranking and policy changes, plus surrogate models for long-term marketplace outcomes.
Model real market mechanics, including auction and bidding dynamics and discovery exposure allocation as a portfolio problem, with allocation to rising sellers.
Improve how a multi-sided live marketplace evaluates changes using off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction.
Help strengthen Whatnot’s external presence through publications, open-source work, and public benchmarks.

What you bring

5+ years of industry experience building and deploying ML models to solve user problems at scale.
Deep expertise in at least one area: recommendation systems, causal inference, off-policy evaluation, reinforcement learning and bandits, auction or 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 such as PyTorch and XGBoost.
Strong grounding in applied statistics, experiment design, and theoretical machine learning.
Strong communication and leadership skills, including the ability to influence roadmaps and align cross-functional teams in a remote environment.
Preferred: experience in two-sided marketplaces, ads and auction systems, or pricing.
Preferred: experience building simulators or economic models of platform behavior.

Tools you’ll use

Python, SQL, PyTorch, XGBoost

Flexible benefits and support

Flexible Time Off Policy and company-wide holidays, including spring and winter break.
Health insurance options: Medical, Dental, Vision.
Work From Home support and a home office setup allowance.
Monthly allowances for cell phone and internet and for wellness.
Annual allowance towards Childcare.
Lifetime benefit for family planning, such as adoption or fertility expenses.
Retirement: 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally.
Monthly allowance to dogfood the app.
Parental Leave: 16 weeks of paid parental leave plus one month gradual return to work.

Compensation

$207,000 to $290,000 per year. For full-time, salary-based US applicants: $207,000/year to $290,000 plus benefits and equity.

Note: Whatnot will only contact candidates through official @whatnot.com email addresses. If you receive an email impersonating a Whatnot recruiter, disregard it and report it as spam.

EOE: Whatnot is an Equal Opportunity Employer.

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26d ago

Senior Machine Learning Engineer

Shipt Remote 🌍 Remote

Remote

26d ago

Full time Artificial Intelligence Data Analysis Engineer

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Job Description

As a Senior Machine Learning Engineer on Shipt’s Foundations team, you will implement advanced machine learning models and help design and analyze experiments that address priority problems across pricing domains. You will operate as a subject matter expert in both machine learning and experimentation, validating how algorithmic changes affect important business metrics.

Key Responsibilities

Implement cutting edge machine learning models to support foundational capabilities.
Design and analyze advanced experiments in collaboration with product, business, and engineering teams to solve key challenges across multiple pricing domains.
Serve as the subject matter expert in a machine learning domain or experimentation.
Build advanced ML solutions and validate the impact of algorithmic changes on key business metrics.
Present recommendations to key stakeholders based on analysis and experimental outcomes.

Required Qualifications

4+ years of experience applying machine learning and statistics in an industry setting, with a record of delivering impactful results.
PhD or Masters in Computer Science, Statistics, or a related field.
Experience building and deploying machine learning models.
Experience with experiment design, rollout, analysis, and reporting.
4+ years of Python development.
Experience presenting to stakeholders.
Experience leading key technical projects and substantially influencing the scope and output of others.
Bachelor's Degree or equivalent experience.

Technology Stack

Python
Artificial Intelligence (AI)
Machine Learning (ML)

Education

PhD or Masters in Computer Science, Statistics, or a related field.

Benefits

Medical, dental, vision and more
401k plan eligibility
Discretionary vacation for exempt team members
Paid holidays throughout the calendar year
Paid sick leave
Eligibility for an annual bonus
Potential for restricted stock units based on role

Work Arrangement

Remote roles: Remote (remote).
Hybrid roles in Birmingham, AL: typically work in-office at least 2 days per week, with core in-office days on Wednesdays and Thursdays.
Hybrid roles in Minneapolis, MN: typically work in-office at least 1 day per week on either Tuesday, Wednesday, or Thursday.
Hybrid roles in San Francisco, CA: typically work in-office at least 1 day per week between Monday and Thursday.
Certain roles may require in-office presence on a full-time basis.

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Machine Learning Experimentation Data Jobs

Machine Learning Engineer, Applied Research

Senior Machine Learning Engineer

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