Staff Machine Learning Engineer, Airbnb
Support Products
$204-259k
More information about location
Community marketplace for holiday accomodation
Job no longer available
Community marketplace for holiday accomodation
1001+ employees
Job no longer available
$204-259k
More information about location
1001+ employees
Company mission
To create a world where anyone can belong anywhere.
Role
Who you are
- 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields
- Strong programming (e.g. Python / Java / Kotlin) and data engineering skills
- Depth of experience in Computer Vision or Natural Language Processing
- Understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection)
- 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 a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models)
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
What the job involves
- The Community Support Platform (CSP) team builds world-class tools for our team of Community Support ambassadors around the world, to ensure our guests and hosts have a great experience on Airbnb, 24/7, and 365 days a year
- Airbnb has a huge global operational staff that must scale with our user base. Our job is as challenging as it is exciting: we own the entire tech stack responsible for their success
- Our team develops the products behind the AirCover and Host-Guest resolutions experience across multiple verticals, including ambassadors tooling, AirCover user-facing claims flows, and intelligent automation and decisioning
- You will develop machine learning approaches to understand our complex data landscape and drive structured insights
- These insights will improve our ability to effectively resolve our customers’ issues and proactively identify process and workflow improvements
- You will collaborate across engineering, data science, product, and operations teams
- These initiatives have high visibility and opportunity for company-wide impact
- Work with large scale structured and unstructured multimodal data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases
- Work collaboratively 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
- Some example projects we have shipped:
- Agent tools to investigate claims and possible fraud through real-time image, text, and user similarity search
- Automated property damage claim item entity extraction
- Advanced analytical data pipelines for monitoring performance, stability, and tool usage
- An advanced ticket routing system to match user issues against available agent skills
Our take
When Airbnb was originally founded, the product helped customers book air mattresses on people's apartment floors. Since then, Airbnb has had over a billion customers hosted through its platform. With more than 4 million registered hosts worldwide, it has grown into a major player in the hospitality sector.
Airbnb has been successful in disrupting the traditional holiday lettings sector. Before it existed accommodation was limited to hotels and bed and breakfasts, but Airbnb has mainstreamed the idea of renting out spare rooms or even entire homes. It has created a new sector of hosts purchasing properties to rent out on the platform and provides a level of flexibility and a range of offerings not previously possible for travelers.
Perhaps a victim of its own success, by 2022 supply of Airbnb-listed properties began to outstrip demand in some markets, as hosts overestimated the appetite for domestic travel. However, the company is still posting strong financials and has unveiled new tools to support its hosts in a tougher rental market. With a healthy bottom line and a huge user base, Airbnb is very likely to overcome the current market turbulence and continue its growth.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
25% employee growth in 12 months
Company
Funding (last 2 of 10 rounds)
Apr 2020
$500m
GROWTH EQUITY VC
Mar 2017
$447.8m
SERIES F
Total funding: $3.8bn
Company benefits
- Paid volunteer time
- Health food and snacks
- Generous parental and family leave
- Learning and development
- Annual travel and experiences credit
Company HQ
Showplace Square, San Francisco, CA
Leadership
Brian Chesky
(Co-Founder & CEO)Previously an Industrial Designer, studying at Rhode Island School of Design.
Nathan Blecharczyk
(Co-Founder & CSO)Studied Computer Science at Harvard, and had around 4 years of professional Software Engineering experience before founding Airbnb, including interning at Microsoft.
Joe Gebbia
(Co-Founder)Also studied Industrial Design at Rhode Island, and previously founded various design-related startups
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