Machine Learning Research

Machine Learning Research Engineer Jobs

2 jobs found

Today

Machine Learning Engineer, Applied Research

Whatnot Seattle, WA 🇺🇸 Remote

Seattle, WA

Today

$210k - $300k/yr Full time Artificial Intelligence Data Analysis Data Science

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Job Description

Lead applied machine learning research that improves live marketplace dynamics at Whatnot, from hypothesis-driven studies through production experimentation.

Responsibilities

Own applied research across marketplace dynamics, including simulation, auction and allocation mechanics, long-term objective modeling, exploration and information value, and marketplace experimentation methods
Drive ideas from hypothesis to production using literature review, prototyping, offline validation, shadow testing, and online experiments launched through partner teams in Discovery and the Seller org
Build system-level models of marketplace behavior, including learned simulators to estimate segment-level effects of ranking and policy changes, plus surrogate models for long-term marketplace outcomes
Model Whatnot’s real market mechanics, covering auction and bidding dynamics and discovery exposure allocation treated as a portfolio problem, including allocation to rising sellers
Improve evaluation for changes in a multi-sided live marketplace using off-policy evaluation, switchback and interference-robust experiment designs, and variance reduction techniques
Strengthen Whatnot’s external technical presence via publications, open-source contributions, and public benchmarks

Requirements

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
Proven track record applying scientific methods to real-world problems on 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 influencing roadmaps and aligning cross-functional teams in a remote environment
Experience with two-sided marketplaces, ads and auction systems, or pricing
Experience building simulators or economic models of platform behavior

Technologies

Python
SQL
PyTorch
XGBoost

Compensation

Full-Time (Salary) US-based applicants: $210,000/year to $300,000/year + benefits + equity
Final salary depends on level, relevant experience, skills, and expertise; the listed range covers base salary only
Compensation Range: $210K - $300K

Benefits

Flexible Time Off Policy and company-wide holidays including a spring and winter break
Health Insurance options including Medical, Dental, Vision
Work From Home Support
Home office setup allowance
Monthly allowance for cell phone and internet
Care benefits
Monthly allowance 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 + one month gradual return to work

Location: Seattle, WA (remote)

Summary: Lead applied ML research for live marketplace dynamics at Whatnot, moving from hypothesis to production and experimentation. Build models and methods for simulation, auction and allocation mechanics, multi-sided evaluation, and contribute to external technical presence.

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

EOE: Whatnot is an Equal Opportunity Employer. They value diversity and do not discriminate on protected characteristics under local law.

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1d ago

Senior/Staff Machine Learning Engineer, 3D Simulation

Zoox Foster City, CA

Foster City, CA

1d ago

$225k - $320k/yr Full time Senior 3d Simulation Ai Ml

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Job Description

Zoox is hiring a Senior/Staff Machine Learning Engineer to advance 3D simulation ML for better variation, fidelity, and support for rare scenario generation.

Responsibilities

Research, implement, and optimize state-of-the-art machine learning methods to improve 3D simulation variation and fidelity
Partner with ML Researchers, Technical Artists, and Simulation engineers to deploy new ML techniques into a production simulator
Train 4D generative models and world models to simulate rare scenarios
Build scalable, usable cloud pipelines for 3D simulation machine learning solutions
Improve rendering and tooling for generating realistic data at scale

Requirements

7+ years of experience in Python/C++ programming and algorithm design
Experience building and extending radiance field ML models
Experience with generative models for 3D or video content
Publications or production experience in human-centric 3D vision, 3D reconstruction, or style transfer
Strong mathematical foundation and understanding of probabilistic techniques

Technologies

Python
C++
Radiance field ML models
Generative models
Cloud computing platforms

Benefits

Paid time off (e.g., sick leave, vacation, bereavement)
Unpaid time off
Zoox Stock Appreciation Rights
Amazon RSUs
Health insurance
Long-term care insurance
Long-term and short-term disability insurance
Life insurance
A sign-on bonus may be offered as part of the compensation package

Bonus Qualifications

Experience automating 3D content pipelines using applications like Houdini, Maya, or Blender
Experience in distributed systems and cloud computing platforms
Experience in generative camera, lidar, radar, or LWIR

Location and Compensation

Location: Foster City, CA (onsite)
Base salary range: USD 225,000 - 320,000 per year
The listed range applies only to base salary; total compensation may include Amazon Restricted Stock Units (RSUs) and Zoox Stock Appreciation Rights
Compensation varies by geographic location and level; leveling is based on factors including relevant experience, domain knowledge, and interview performance

Accommodations

If you need an accommodation to participate in the application or interview process, contact accommodations@zoox.com or your assigned recruiter

AI Tools Statement

Zoox may use AI tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses
These tools assist the recruitment team but do not replace human judgment
If you would like more information about how your data is processed, contact Zoox

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Machine Learning Research Engineer Jobs

Machine Learning Engineer, Applied Research

Senior/Staff Machine Learning Engineer, 3D Simulation

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