Senior Staff Machine Learning Engineer
Trust
Posted on 1/31/2024
INACTIVE
Airbnb

10,001+ employees

Online marketplace for people to list, discover, and book accommodations
Company Overview
Airbnb's mission is to create a world where anyone can belong anywhere and we are focused on creating an end-to-end travel platform that will handle every part of your trip. The company is building a worldwide timeshare marketplace.
Consumer Goods

Company Stage

N/A

Total Funding

$10B

Founded

2007

Headquarters

San Francisco, California

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

3%
Locations
Remote in USA
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Kubernetes
Python
Airflow
Tensorflow
Data Structures & Algorithms
Pytorch
Apache Spark
Apache Kafka
Java
Scala
Apache Hive
CategoriesNew
AI & Machine Learning
Software Engineering
Requirements
  • 12+ years of industry experience in applied Machine Learning
  • Bachelor’s, Master’s or PhD in CS/ML or related field
  • Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering skills
  • Deep understanding of Machine Learning best practices, algorithms, and domains
  • Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (eg. Hive)
  • Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models
  • Exposure to architectural patterns of large, high-scale software applications
  • Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
  • Experience with the Trust and Risk domain is a plus
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
  • Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists
  • Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks
  • Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases
Desired Qualifications
  • Experience with the Trust and Risk domain