Full-Time

Staff Machine Learning Engineer

Marketing Technology

Confirmed live in the last 24 hours

Airbnb

Airbnb

10,001+ employees

Online marketplace for lodging and experiences

Government & Public Sector
Real Estate

Compensation Overview

$204k - $259kAnnually

+ Bonus + Equity + Benefits + Employee Travel Credits

Expert

Company Historically Provides H1B Sponsorship

United States

Occasional work at an Airbnb office or attendance at offsites may be required.

Category
Applied Machine Learning
Deep Learning
AI & Machine Learning
Required Skills
Python
Java
Scala
C/C++
Requirements
  • 9+ years of industry experience in applied Machine Learning with a BS/Masters or 7+ years with a PhD
  • Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills
  • Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization).
  • Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
  • Preferred Qualifications: Hands on experience with advanced Machine Learning Techniques, including but not limited to reinforcement learning, deep learning, and large language models (LLM).
Responsibilities
  • Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases.
  • Collaborate with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
  • Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
  • Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable and high-performing Machine Learning systems.

Airbnb operates an online marketplace that connects travelers with hosts offering lodging and unique tourism experiences. The platform allows hosts to list their properties, which can range from single rooms to entire homes, enabling guests to book accommodations that provide a more authentic local experience. Airbnb earns revenue through a commission system, taking a percentage from each booking made on its platform. With a presence in nearly every country and over 5 million hosts, Airbnb has facilitated more than 1.5 billion guest arrivals. Additionally, the platform offers various local experiences organized by hosts, allowing guests to engage in activities that enhance their travel adventures.

Company Stage

IPO

Total Funding

$3.7B

Headquarters

San Francisco, California

Founded

2007

Growth & Insights
Headcount

6 month growth

13%

1 year growth

40%

2 year growth

77%
Simplify Jobs

Simplify's Take

What believers are saying

  • Rising 'workation' trends increase demand for longer stays on Airbnb.
  • Eco-friendly accommodations attract environmentally conscious travelers to Airbnb's platform.
  • Digital nomadism expansion boosts Airbnb bookings with flexible living arrangements.

What critics are saying

  • Legal challenges in Spain could lead to fines and operational restrictions for Airbnb.
  • Airbnb faces vulnerabilities in property vetting due to bank fraud incidents in Europe.
  • Regulatory scrutiny in Ghana may impact Airbnb's growth and operations in the region.

What makes Airbnb unique

  • Airbnb offers unique stays and experiences, unlike traditional hotel accommodations.
  • The platform connects hosts and guests globally, facilitating diverse lodging options.
  • Airbnb's commission-based model incentivizes hosts to list properties and monetize assets.

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Benefits

Comprehensive health plans

Paid volunteer time

Healthy food and snacks

Generous parental and family leave

Learning and development

Annual travel and experiences credit