Senior Machine Learning Engineer, Airbnb
Trust
$191-223k
More information about location
Community marketplace for holiday accomodation
Be an early applicant
Community marketplace for holiday accomodation
1001+ employees
Be an early applicant
$191-223k
More information about location
1001+ employees
Company mission
To create a world where anyone can belong anywhere.
Role
Who you are
- 5+ years of industry experience in software engineering, with a focus on applied Machine learning
- BS/MS/PhD in Computer Science, a related field, or equivalent work experience
- Strong programming (Scala / Python / Java/ C++ or equivalent) skills
- Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection)
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models
- Strong collaboration skills and experience working with cross-functional teams
- Comfortable navigating ambiguity and driving projects from concept to production
- Experience with test driven development, familiar with A/B testing, incremental delivery and deployment
- Experience with computer vision systems (e.g., face detection, liveness, tampering detection) is a plus
- Experience with the Trust and Risk domain is a plus
What the job involves
- The Identity Defense team plays a critical role in safeguarding Airbnb’s platform by ensuring that every user is who they say they are
- We are responsible for preventing identity misuse, detecting fraudulent and duplicate accounts, and enforcing policies against underage use
- We operate at the intersection of backend engineering, machine learning, and computer vision to deliver defenses at scale—while minimizing friction for trusted users
- Identity Misuse Detection - Fraudsters increasingly use fake, stolen, or AI-generated identities to gain access to the platform
- Traditional verification signals are no longer enough in the face of sophisticated tampering techniques like deepfakes and synthetic imagery
- Our team builds advanced detection systems that combine machine learning, computer vision, and biometric signals to identify and stop bad actors in real time
- We continuously evolve our models and systems to keep pace with rapidly advancing AI-driven attack vectors, ensuring Airbnb stays one step ahead
- Duplicate Account Prevention - Airbnb’s integrity depends on enforcing the principle of one account per person
- We’re tackling this using identity linking methods that combine graph-based analysis, embeddings, and device IDs
- The scale, complexity, and ambiguity of identity data make this one of the most technically demanding problems at Airbnb
- Underage User Enforcement - Airbnb prohibits users under the age of 18 from accessing the platform, but verifying age accurately—especially across global markets and varying document types—is a nuanced challenge
- Fraudsters exploit OCR weaknesses or use borrowed identities to circumvent our policy
- We are investing in government ID parsing improvements, tampering detection, and more robust age inference methods to ensure compliance while minimizing false positives
- This space also requires deep collaboration with legal and policy teams to ensure regulatory alignment and defensibility across regions
- Train and deploy machine learning models for identity misuse detection and risk scoring
- Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases
- Integrate advanced verification methods, including biometrics and NFC-based flows
- Collaborate closely with ML, iOS/Android, and web engineers to deliver end-to-end solutions
- 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
- Contribute to foundational infrastructure including secure data handling, image processing, model serving, and feature engineering
- Shape technical direction and influence the team roadmap through long-term strategy and investment planning
- Mentor other engineers and promote best practices to strengthen Airbnb’s engineering culture and foundations
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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